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Guo, Yanjun, Terri Starman, and Charles Hall. "Growth, Quality, and Economic Value Responses of Bedding Plants to Reduced Water Usage." HortScience 54, no. 5 (2019): 856–64. http://dx.doi.org/10.21273/hortsci13793-18.
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This study analyzed the effects of two ranges of drying down of substrate moisture content (SMC) before re-watering on plant growth and development, postproduction quality, and economic value of bedding plants grown in 1.67-L containers during greenhouse production. The two SMC treatments were wide-range (WR) SMC (WR-SMC) for dry-down from container capacity (CC) of 54% SMC dried down to 20% SMC or narrow-range (NR) SMC (NR-SMC) for dry-down from CC of 54% SMC dried down to 40% SMC. Six bedding plant cultivars were used [Solenostemon scutellarioides ‘French Quarter’ (coleus); Petunia ×hybrida ‘Colorworks Pink Radiance’ (petunia); Lantana camara ‘Lucky Flame’ (lantana); Impatiens ×hybrida ‘Sunpatiens Compact Hot Coral’ (SCC); ‘Sunpatiens Spreading Lavender’ (SSL) (impatiens); and Salvia splendens ‘Red Hot Sally II’ (salvia)]. Shoot dry weight was reduced with WR-SMC on petunia, lantana, impatiens SCC, and salvia at the end of production. With WR-SMC, the petunia and impatiens SCC root ball coverage percentages were greater on the bottom of the container, whereas those of impatiens SSL and salvia were reduced. The WR-SMC increased petunia postproduction quality by increasing the flower number. Lantana and impatiens SCC inflorescence/flower and/or bud number were reduced with WR-SMC. The impatiens SSL flower number was unaffected by SMC treatment. Salvia grown with WR-SMC had increased postproduction quality. WR-SMC reduced postproduction water potential in petunia, lantana, and coleus, suggesting that plants with WR-SMC during production were acclimated to reduced irrigation administered during postproduction. WR-SMC saved labor due to less frequent watering and overhead-associated costs due to reduced bench space, with the exception of coleus and impatiens SSL, which used the same bench space as NR-SMC. Considering production and/or postproduction quality, using WR-SMC during greenhouse production is beneficial as an irrigation method for coleus, petunia, impatiens SSL, and salvia, but not for impatiens SCC or lantana grown in 1.67-L containers.
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Wang, Liangliang, Shijia Wang, and Alexandre Bouchard-Côté. "An Annealed Sequential Monte Carlo Method for Bayesian Phylogenetics." Systematic Biology 69, no. 1 (2019): 155–83. http://dx.doi.org/10.1093/sysbio/syz028.
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Abstract We describe an “embarrassingly parallel” method for Bayesian phylogenetic inference, annealed Sequential Monte Carlo (SMC), based on recent advances in the SMC literature such as adaptive determination of annealing parameters. The algorithm provides an approximate posterior distribution over trees and evolutionary parameters as well as an unbiased estimator for the marginal likelihood. This unbiasedness property can be used for the purpose of testing the correctness of posterior simulation software. We evaluate the performance of phylogenetic annealed SMC by reviewing and comparing with other computational Bayesian phylogenetic methods, in particular, different marginal likelihood estimation methods. Unlike previous SMC methods in phylogenetics, our annealed method can utilize standard Markov chain Monte Carlo (MCMC) tree moves and hence benefit from the large inventory of such moves available in the literature. Consequently, the annealed SMC method should be relatively easy to incorporate into existing phylogenetic software packages based on MCMC algorithms. We illustrate our method using simulation studies and real data analysis.
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Abbasi, Saad Jamshed, Won Jae Kim, Jaehyung Kim, Min Cheol Lee, Byeong Ju Lee, and Myung Jun Shin. "Robust Control Design of a Human Heart Rate System for Cardiac Rehabilitation Exercise." Electronics 11, no. 24 (2022): 4081. http://dx.doi.org/10.3390/electronics11244081.
Texte intégralRésumé :
Automatic, precise, and accurate heart rate control during treadmill exercise is an interesting topic among researchers. The human heart is a highly nonlinear system. Conventional control techniques are not sufficient and it is difficult to accurately model the human heart. Two different robust controllers were designed for this nonlinear system. Firstly, sliding mode control (SMC) was implemented; SMC is robust against parametric uncertainties and external disturbance but its robustness is not guaranteed during the reaching phase, especially in heart rate control, and implementation of SMC requires the linear parameters of the system (human heart rate model). In this research, the signal compression method (SCM) was used for approximately linearized modeling of the human heart rate. The extraction of the human heart rate model using SCM requires experiment and computation. Furthermore, it was observed in this research that SCM is not a precise method. Therefore, integral sliding mode control (ISMC) was designed and implemented to overcome these difficulties. By introducing an auxiliary sliding surface, the reaching phase and effect of the perturbation on an actual sliding surface were eliminated; furthermore, implementation of ISMC does not require the linear parameters of the system. Simulations were performed in MATLAB/Simulink and experiments were conducted in a hospital. Six clinical subjects participated in this experiment. Both forms of control logic were implemented during the desired heart rate tracking test. Results showed that the desired heart rate tracking of ISMC is better than that of SMC. The tracking error of ISMC is smaller than that of SMC. However, ISMC control output has chattering, which needs to be reduced.
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Xing, Minfeng, Lin Chen, Jinfei Wang, Jiali Shang, and Xiaodong Huang. "Soil Moisture Retrieval Using SAR Backscattering Ratio Method during the Crop Growing Season." Remote Sensing 14, no. 13 (2022): 3210. http://dx.doi.org/10.3390/rs14133210.
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Soil moisture content (SMC) is an indispensable basic element for crop growth and development in agricultural production. Obtaining accurate information on SMC in real time over large agricultural areas has important guiding significance for crop yield estimation and production management. In this study, the paper reports on the retrieval of SMC from RADARSAT-2 polarimetric SAR data. The proposed SMC retrieval algorithm includes vegetation correction based on a ratio method and roughness correction based on the optimal roughness method. Three vegetation description parameters (i.e., RVI, LAI, and NDVI) serve as vegetation descriptors in the parameterization of the algorithm. To testify the vegetation correction result of the algorithm, the water cloud model (WCM) was compared with the algorithm. The calibrated integrated equation model (CIEM) was employed to describe the backscattering from the underlying soil. To improve the accuracy of SMC retrieval, the CIEM model was optimized by using the optimal roughness parameter and the normalization method of reference incidence angle. Validation against ground measurements showed a high correlation between the measured and estimated SMC when the NDVI serves as vegetation descriptor (R2 = 0.68, RMSE = 4.15 vol.%, p < 0.01). The overall estimation performance of the proposed SMC retrieval algorithm is better than that of the WCM. It demonstrates that the proposed algorithm has an operational potential to estimate SMC over wheat fields during the growing season.
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Pošković, Emir, Fausto Franchini, Luca Ferraris, Federico Carosio, and Marco Actis Grande. "Rapid Characterization Method for SMC Materials for a Preliminary Selection." Applied Sciences 11, no. 24 (2021): 12133. http://dx.doi.org/10.3390/app112412133.
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In electrical machines, laminated steels are commonly adopted as soft magnetic materials, while for permanent magnets, sintered ferrites and NdFeB are the most common solutions. On the other hand, the growing demand for volume reduction with the increment of efficiency leads to the necessity of exploring other magnetic materials able to face the challenge better than the traditional ones. Bonded magnets have been used to replace sintered magnets, obtaining a better use of space and particular magnetic properties. Instead, for the magnetic circuit, Soft Magnetic Composites (SMC) allow realizing very complex magnetic design (3D path for flux) with iron loss reduction at medium-high frequencies, especially for the eddy currents loss contribution. On the other hand, SMC materials have such drawbacks as low mechanical properties and high hysteresis losses. For this reason, in this work, different studies considering several variables have been carried out. SMCs were produced through a moulding process; inorganic and organic layers to cover ferromagnetic particles were used, adopting different coating processes. Particular tests have been performed for a quicker and more indicative overview of the materials obtained. The single sheet tester (SST) is easier than traditional toroidal methods; on the other hand, the multiplicity of variables affects the SMC materials and their process. For this reason, coercivity and conductibility tests permit rapid measurement and provide a direct classification of the produced SMCs, providing the main information needed to select suitable materials. Results highlighted that choosing the more appropriate SMC material is possible after using these simple preliminary tests. After these tests, it was possible to argue that with 0.2 wt% of phenolic resin as the organic layer (and compaction pressure of 800 MPa), it is possible to produce a good SMC. On the other hand, the SMC with 0.2 wt% of epoxy resin (and compaction pressure of 800 MPa) gives a minor coercivity value. Additionally, despite the SMC with the inorganic layer, 0.2 wt% of nano-ferrites showing the best coercivity values (specifically for vacuum treatment at 600 °C), their resistivity was unsatisfactory.
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Kolesnikov, A. A., and A. A. Kuz’menko. "Sliding Mode Control Laws Design by the ADAR Method with Subsequent Invariant Manifolds Aggregation." Mekhatronika, Avtomatizatsiya, Upravlenie 20, no. 8 (2019): 451–60. http://dx.doi.org/10.17587/mau.20.451-460.
Texte intégralRésumé :
Sliding mode control (SMC) laws are commonly used in engineering to make a system robust to parameters change, external disturbances and control object unmodeled dynamics. State-of-the-art capabilities of the theory of adaptive and robust control, the theory of fuzzy systems, artificial neural networks, etc., which are combined with SMC, couldn’t resolve current issues of SMC design: vector design and stability analysis of a closed-loop system with SMC are involved with considerable complexity. Generally the classical problem of SMC design consists in solving subtasks for transit an object from an arbitrary initial position onto the sliding surface while providing conditions for existence of a sliding mode at any point of the sliding surface as well as ensuring stable movement to the desired state. As a general rule these subtasks are solved separately. This article presents a methodology for SMC design based on successive aggregation of invariant manifolds by the procedure of method of Analytical Design of Aggregated Regulators (ADAR) from the synergetic control theory. The methodology allows design of robust control laws and simultaneous solution of classical subtasks of SMC design for nonlinear objects. It also simplifies the procedure for closed-loop system stability analyze: the stability conditions are made up of stability criterions for ADAR method functional equations and the stability criterions for the final decomposed system which dimension is substantially less than dimension of the initial system. Despite our paper presents only the scalar SMC design procedure in details, the ideas are also valid for vector design procedure: the main difference is in the number of invariant manifolds introduced at the first and following stages of the design procedure. The methodology is illustrated with design procedure examples for nonlinear engineering systems demonstrating the achievement of control goals: hitting to target invariants, insensitivity to emerging parametric and external disturbances.
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Li, Zhi, Bo You, Liang Ding, Haibo Gao, and Fengxiang Huang. "Trajectory Tracking Control for WMRs with the Time-Varying Longitudinal Slippage Based on a New Adaptive SMC Method." International Journal of Aerospace Engineering 2019 (August 20, 2019): 1–13. http://dx.doi.org/10.1155/2019/4951538.
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Wheeled mobile robots (WMRs) in real complex environments such as on extraterrestrial planets are confronted with uncertain external disturbances and strong coupling of wheel-ground interactions while tracking commanded trajectories. Methods based on sliding mode control (SMC) are popular approaches for these situations. Traditional SMC has some potential problems, such as slow convergence, poor robustness, and excessive output chattering. In this paper, a kinematic-based feed-forward control model is designed for WMRs with longitudinal slippage and applied to the closed-loop control system for active compensation of time-varying slip rates. And a new adaptive SMC method is proposed to guide a WMR in trajectory tracking missions based on the kinematic model of a general WMR. This method combines the adaptive control method and a fast double-power reaching law with the SMC method. A complete control loop with active slip compensation and adaptive SMC is thus established. Simulation results show that the proposed method can greatly suppress chattering and improve the robustness of trajectory tracking. The feasibility of the proposed method in the real world is demonstrated by experiments with a skid-steered WMR on the loose-soil terrain.
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Doğan, Mustafa, and Ümit Önen. "TRAJECTORY TRACKING CONTROL OF A TWO WHEELED SELF-BALANCING ROBOT BY USING SLIDING MODE CONTROL." Konya Journal of Engineering Sciences 12, no. 3 (2024): 652–70. http://dx.doi.org/10.36306/konjes.1425949.
Texte intégralRésumé :
Two-Wheeled Self-Balancing Robots are widely used in various fields today. These systems have a highly unstable nature due to their underactuated structures. On the other hand, parameter uncertainties and external disturbances significantly affect their control performance. The best way to deal with parameter uncertainties that can easily lead controllers to instability is to use robust control methods. Dealing with these uncertainties is particularly crucial in control of underactuated and unstable systems such as Two-Wheeled Self-Balancing Robots. In this study, trajectory tracking control of a two wheeled self-balancing robot by using Sliding Mode Control (SMC) was realized. The chattering problem inherent in the SMC method was eliminated by employing tangent hyperbolic (tanh) switching function instead of signum function. The performance of the SMC controller has been examined under five different cases including external disturbance and various parameter uncertainties and compared with PID and LQR methods. The results showed that the SMC method is much more insensitive to parameter changes than the PID and LQR methods. It has also been observed that all three controllers maintain their stability against disturbance inputs, but the SMC method offers a better control performance.
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Li, Zeyu, Weidong Liu, Le Li, Wenbo Zhang, and Liwei Guo. "Path following method for AUV based on Q-Learning and RBF neural network." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 39, no. 3 (2021): 477–83. http://dx.doi.org/10.1051/jnwpu/20213930477.
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In the underwater docking process, the oscillation on AUV velocity brings extra challenge on AUV path following. A Q-learning based Sliding Mode Control (SMC) method to increase the path following performances is proposed. Firstly, AUV guidance law is designed to reduce the path following error. Heading and depth sliding mode controllers are designed to track the guidance law. Then, according to AUV velocity, tracking error and the first derivative, the control parameters of SMC are optimized via Q-learning network. RBF neural network is built to accelerate the offline learning rate. Finally, numerical simulations are made to investigate the characteristics of the present method. Comparisons are made between the trained Q-learning based SMC and the traditional SMC. The results show the effectiveness of the present method.
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Farhat, Maissa, and Oscar Barambones. "Advanced Control Scheme Optimization for Stand-Alone Photovoltaic Water Pumping Systems." Computation 12, no. 11 (2024): 224. http://dx.doi.org/10.3390/computation12110224.
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This study introduces a novel method for controlling an autonomous photovoltaic pumping system by integrating a Maximum Power Point Tracking (MPPT) control scheme with variable structure Sliding Mode Control (SMC) alongside Perturb and Observe (P&O) algorithms. The stability of the proposed SMC method is rigorously analyzed using Lyapunov’s theory. Through simulation-based comparisons, the efficacy of the SMC controller is demonstrated against traditional P&O methods. Additionally, the SMC-based system is experimentally implemented in real time using dSPACE DSP1104, showcasing its robustness in the presence of internal and external disturbances. Robustness tests reveal that the SMC controller effectively tracks Maximum Power Points (MMPs) despite significant variations in load and solar irradiation, maintaining optimal performance even under challenging conditions. The results indicate that the SMC system can achieve up to a 70% increase in water flow rates compared with systems without MPPT controllers. Furthermore, SMC demonstrated high sensitivity to sudden changes in environmental conditions, ensuring efficient power extraction from the photovoltaic panels. This study highlights the advantages of integrating SMC into Photovoltaic Water Pumping Systems (PV-WPSs), providing enhanced control capabilities and optimizing system performance. The findings contribute to the development of sustainable water supply solutions, particularly in remote areas with limited access to the electrical grid.
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Sheikhi Jouybary, Homa, Davood Arab Khaburi, Ahmed El Hajjaji, and Augustin Mpanda Mabwe. "Optimal Sliding Mode Control of Modular Multilevel Converters Considering Control Input Constraints." Energies 18, no. 11 (2025): 2757. https://doi.org/10.3390/en18112757.
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This paper investigates the optimal sliding mode control (SMC) of modular multilevel converters (MMCs) by considering control input constraints. Conventional SMC methods for MMCs typically overlook the system’s constraints. To address this, an optimal SMC approach that incorporates control input constraints through quadratic programming (QP) is proposed. The control design problem is formulated in a constrained optimization framework and solved using the infeasible active-set (IAS) method to efficiently achieve the optimal solution. By applying optimal SMC, this work contributes to the advancement of SMC strategies for MMCs by addressing both constraints and performance optimization in a systematic way. This is particularly relevant for real-world applications, where controllers may temporarily exceed their limits before enforcing constraints. To validate the proposed approach, a comparative analysis with conventional SMC methods is performed, and simulation results confirm that the proposed approach provides improved performance.
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Suprapto, Suprapto, Masduki Zakarijah, and Muslikhin Muslikhin. "Adaptive fuzzy sliding mode controller for a single-stage inverted pendulum." International Journal of Advances in Applied Sciences 11, no. 4 (2022): 324. http://dx.doi.org/10.11591/ijaas.v11.i4.pp324-334.
Texte intégralRésumé :
Sliding mode controller (SMC) has become a popular traditional control method in industries due to the most effective control strategies employing nonlinear control and the ability to reject disturbances, particularly for line trajectory control. However, this control method has chattering problems due to high-frequency switching. To cope with the shortcoming, an artificial intelligence (AI) method is utilized in the traditional SMC to eliminate or reduce this chattering problem. This paper investigates an adaptive fuzzy logic system combined with SMC algorithm to alleviate the problem. Fuzzy logic is chosen due to its advantages in tackling nonlinear properties using if-then thinking, whereas SMC method can be applied due to its ability to reject disturbance control. The inverted pendulum is selected as a controlled object and simulated using MATLAB/Simulink to investigate this control method. By combining the fuzzy logic system and the SMC approach, the chattering problems can be adaptively reduced on the line trajectory tracking signal. The adaptive fuzzy SMC achieved better performance with fast response compared with previous literature algorithms for similar plants.
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Suprapto, Zakarijah Masduki, and Muslikhin. "Adaptive fuzzy sliding mode controller for a single-stage inverted pendulum." International Journal of Advances in Applied Sciences (IJAAS) 11, no. 4 (2022): 324–34. https://doi.org/10.11591/ijaas.v11.i4.pp324-334.
Texte intégralRésumé :
Sliding mode controller (SMC) has become a popular traditional control method in industries due to the most effective control strategies employing nonlinear control and the ability to reject disturbances, particularly for line trajectory control. However, this control method has chattering problems due to high-frequency switching. To cope with the shortcoming, an artificial intelligence (AI) method is utilized in the traditional SMC to eliminate or reduce this chattering problem. This paper investigates an adaptive fuzzy logic system combined with SMC algorithm to alleviate the problem. Fuzzy logic is chosen due to its advantages in tackling nonlinear properties using if-then thinking, whereas SMC method can be applied due to its ability to reject disturbance control. The inverted pendulum is selected as a controlled object and simulated using MATLAB/Simulink to investigate this control method. By combining the fuzzy logic system and the SMC approach, the chattering problems can be adaptively reduced on the line trajectory tracking signal. The adaptive fuzzy SMC achieved better performance with fast response compared with previous literature algorithms for similar plants.
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Li, Wangyang, Youzhen Xiang, Xiaochi Liu, et al. "Estimation of Soil Moisture Content Based on Fractional Differential and Optimal Spectral Index." Agronomy 14, no. 1 (2024): 184. http://dx.doi.org/10.3390/agronomy14010184.
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Applying hyperspectral remote sensing technology to the prediction of soil moisture content (SMC) during the growth stage of soybean emerges as an effective approach, imperative for advancing the development of modern precision agriculture. This investigation focuses on SMC during the flowering stage under varying nitrogen application levels and film mulching treatments. The soybean canopy’s original hyperspectral data, acquired at the flowering stage, underwent 0–2-order differential transformation (with a step size of 0.5). Five spectral indices exhibiting the highest correlation with SMC were identified as optimal inputs. Three machine learning methods, namely support vector machine (SVM), random forest (RF), and back propagation neural network (BPNN), were employed to formulate the SMC prediction model. The results indicate the following: (1) The correlation between the optimal spectral index of each order, obtained after fractional differential transformation, and SMC significantly improved compared to the original hyperspectral reflectance data. The average correlation coefficient between each spectral index and SMC under the 1.5-order treatment was 0.380% higher than that of the original spectral index, with mNDI showing the highest correlation coefficient at 0.766. (2) In instances of utilizing the same modeling method with different input variables, the SMC prediction model’s accuracy follows the order: 1.5 order > 2.0 order > 1.0 order > 0.5 order > original order. Conversely, with consistent input variables and a change in the modeling method, the accuracy order becomes RF > SVM > BPNN. When comprehensively assessing model evaluation indicators, the 1.5-order differential method and RF method emerge as the preferred order differential method and model construction method, respectively. The R2 for the optimal SMC estimation model in the modeling set and validation set were 0.912 and 0.792, RMSEs were 0.005 and 0.004, and MREs were 2.390% and 2.380%, respectively. This study lays the groundwork for future applications of hyperspectral remote sensing technology in developing soil moisture content estimation models for various crop growth stages and sparks discussions on enhancing the accuracy of these different soil moisture content estimation models.
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Cha, Hyun Rok, K. S. Lee, Cheol Ho Yun, Hyeon Taek Son, and Tea Uk Jung. "A Considering Method of Density Distribution Factor for the Ceramic Motor with Soft Magnetic Composite Core." Key Engineering Materials 368-372 (February 2008): 211–14. http://dx.doi.org/10.4028/www.scientific.net/kem.368-372.211.
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In this paper, we suggested the new standards of motor design in using of Soft magnetic composite (SMC) material. Previous motor design in using of SMC material executed the same procedures of silicon steel. These procedures assumed that all places of material have the same density distribution and B-H curves. But we showed that the SMC material has inequality density distribution. By using powder forming analysis with FEM analysis, we showed that difference of density distribution could not be avoided because of the shear stress on powder, surface of the mold and punch. Therefore the magnetic characteristic was not the same in all places of material. So, we suggested the new method of motor design which considered the inequality density distribution in using of SMC material. And we compared previous method results and new method results and showed the differences of the result values. The density deviation of the SMC motor core was 5.8% and efficiency deviation was 3%. Especially the output value was different above 11% when we got the results by using previous method.
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Yao, Yadong, Jixuan Yan, Guang Li, et al. "A GNSS-IR Soil Moisture Inversion Method Considering Multi-Factor Influences Under Different Vegetation Covers." Agriculture 15, no. 8 (2025): 837. https://doi.org/10.3390/agriculture15080837.
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The Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) has demonstrated significant potential for soil moisture content (SMC) monitoring due to its high spatiotemporal resolution. However, GNSS-IR inversion experiments are notably influenced by vegetation and meteorological factors. To address these challenges, this study proposes a multi-factor SMC inversion method. Six GNSS stations from the Plate Boundary Observatory (PBO) were selected as study sites. A low-order polynomial was applied to separate the reflected signals, extracting parameters such as phase, frequency, amplitude, and effective reflector height. Auxiliary variables, including the Normalized Microwave Reflection Index (NMRI), cumulative rainfall, and daily average evaporation, were used to further improve inversion accuracy. A multi-factor SMC inversion dataset was constructed, and three machine learning models were selected to develop the SMC prediction model: Support Vector Regression (SVR), suitable for small and medium-sized regression tasks; Convolutional Neural Networks (CNN), with robust feature extraction capabilities; and NRBO-XGBoost, which supports automatic optimization. The multi-factor SMC inversion method achieved remarkable results. For instance, at the P038 station, the model attained an R2 of 0.98, with an RMSE of 0.0074 and an MAE of 0.0038. Experimental results indicate that the multi-factor inversion model significantly outperformed the traditional univariate model, whose R2 (RMSE, MAE) was only 0.88 (0.0179, 0.0136). Further analysis revealed that NRBO-XGBoost surpassed the other models, with its average R2 outperforming SVR by 0.11 and CNN by 0.03. Additionally, the analysis of different surface types showed that the method achieved higher accuracy in grassland and open shrubland areas, with all models reaching R2 values above 0.9. Therefore, the accuracy of the multi-factor SMC inversion model was validated, supporting the practical application of GNSS-IR technology in SMC inversion.
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Tang, Aihua, Lin Yang, Tao Zeng, and Quanqing Yu. "Cascade Control Method of Sliding Mode and PID for PEMFC Air Supply System." Energies 16, no. 1 (2022): 228. http://dx.doi.org/10.3390/en16010228.
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Proton exchange membrane fuel cells (PEMFC) are vulnerable to oxygen starvation when working under variable load. To address these issues, a cascade control strategy of sliding mode control (SMC) and Proportion Integration Differentiation (PID) control is proposed in this study. The goal of the control strategy is to enhance the PEMFC’s net power by adjusting the oxygen excess ratio (OER) to the reference value in the occurrence of a load change. In order to estimate the cathode pressure and reconstruct the OER, an expansion state observer (ESO) is developed. The study found that there is a maximum error of about 2200Pa between the estimated cathode pressure and the actual pressure. Then the tracking of the actual OER to the reference OER is realized by the SMC and PID cascade control. The simulation study, which compared the control performance of several methods—including PID controller, adaptive fuzzy PID controller and the proposed controller, i.e., the SMC and PID cascade controller—was carried out under various load-changing scenarios. The outcomes demonstrate that the proposed SMC and PID cascade controller method really does have a faster response time. The overshoot is reduced by approximately 3.4% compared to PID control and by about 0.09% compared to fuzzy adaptive PID. SMC and PID cascade control reference OER performs more effectively in terms of tracking compared to PID control and adaptive fuzzy PID control .
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Wei, Yuhao, Li Sun, and Zhongxian Chen. "An Improved Sliding Mode Control Method to Increase the Speed Stability of Permanent Magnet Synchronous Motors." Energies 15, no. 17 (2022): 6313. http://dx.doi.org/10.3390/en15176313.
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A permanent magnet synchronous motor (PMSM) plays an important role in the operation performance of an electric vehicle. In order to increase the speed stability of PMSMs, an improved sliding mode control (SMC) method is proposed in this paper. Firstly, the control process of a PMSM is divided into parts, which are the torque closed-loop control and speed closed-loop control. Secondly, an integrated control method with proportional integral (PI) and inverter switching frequency is adopted in order to increase the torque performance of the PMSM. Lastly, compared with the traditional SMC method, an improved SMC method with saturation function is proposed in order to decrease the speed fluctuation of the PMSM from 7.7% to 5.9%, thereby increasing the speed stability of the PMSM. The results of the experimental test indicate that both the speed stability and starting performance of the PMSM are increased by the improved SMC method.
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Hou, Xianmin, and Songyu Wang. "Composite Learning Sliding Mode Control of Nonlinear Systems Subject to Actuator Failures." Journal of Mathematics 2020 (December 7, 2020): 1–7. http://dx.doi.org/10.1155/2020/6665599.
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This article focuses on controlling single-input-single-output (SISO) nonlinear systems with actuator failures via sliding mode control (SMC) and composite learning SMC (CLSMC). In the design of the SMC, an integer-order sliding surface is proposed, and an adaptive law is constructed to update the parameter evaluation in the actuator failure. The SMC method can achieve the tracking error approaching zero if a strict permanent excitation (PE) condition is satisfied. To mitigate this requirement, by using all data recorded while the controller works, we construct prediction errors that are utilized to produce a composite learning adaptive law. Then, the proposed CLSMC method not only drives the tracking error to zero but also realizes the accurate evaluation of the unmatched unknown parameter in the actuator failure. In addition, in the proposed CLSMC method, we only need to satisfy an interval excitation (IE) condition. Simulation results are presented to indicate the validity of our methods.
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Deng, Yue, Yongzhen Pei, Changguo Li, and Bin Zhu. "Model Selection and Parameter Estimation for an Improved Approximate Bayesian Computation Sequential Monte Carlo Algorithm." Discrete Dynamics in Nature and Society 2022 (June 30, 2022): 1–14. http://dx.doi.org/10.1155/2022/8969903.
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Model selection and parameter estimation are very important in many fields. However, the existing methods have many problems, such as low efficiency in model selection and inaccuracy in parameter estimation. In this study, we proposed a new algorithm named improved approximate Bayesian computation sequential Monte Carlo algorithm (IABC-SMC) based on approximate Bayesian computation sequential Monte Carlo algorithm (ABC-SMC). Using the IABC-SMC algorithm, given data and the set of two models including logistic and Gompertz models of infectious diseases, we obtained the best fitting model and the values of unknown parameters of the corresponding model. The simulation results showed that the IABC-SMC algorithm can quickly and accurately select a model that best matches the corresponding epidemic data among multiple candidate models and estimate the values of unknown parameters of model very accurately. We further compared the effects of IABC-SMC algorithm with that of ABC-SMC algorithm. Simulations showed that the IABC-SMC algorithm can improve the accuracy of estimated parameter values and the speed of model selection and also avoid the shortage of ABC-SMC algorithm. This study suggests that the IABC-SMC algorithm can be seen as a promising method for model selection and parameter estimation.
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Vo, Hau Huu. "Sliding Mode Speed Controller Design for Field Oriented Controlled PMSM Drive of an Electric Vehicle." Journal of Advanced Engineering and Computation 7, no. 3 (2023): 164. http://dx.doi.org/10.55579/jaec.202373.414.
Texte intégralRésumé :
The paper deals with an application of sliding mode control (SMC) in speed controller of field oriented controlled permanent magnet synchronous motor (PMSM) for a simplified model of an electrical vehicle. For the simplified one, zero-pole elimination method is utilized to design speed controller because of its simplicity. However, the method brings large integral constant time that makes speed response slow. In order to provide fast and robust-to-noise speed one, the SMC method is utilized to replace the zero-pole elimination (ZPE) one. Simulations at wide range of reference speed and load torque are carried out. Performance indices including steady-state error, overshoot and undershoot are employed to assess the speed controller design methods. Evaluated results confirm that the proposed SMC gives smaller performance indices than the ZPE method.
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Zhou, Tao, and Xi Feng Liang. "Position Sliding Mode Control of Manipulator Joint Based on Genetic Algorithm." Advanced Materials Research 912-914 (April 2014): 727–31. http://dx.doi.org/10.4028/www.scientific.net/amr.912-914.727.
Texte intégralRésumé :
In order to improve the control performance of position trajectory tracking of manipulator joint, a sliding mode control (SMC) method based on genetic algorithm(GA) is proposed in this paper. In this method, the performance of SMC algorithm is improved through adjusting the parameters of switching function and exponential approach law by genetic algorithm. The method was applied to accomplish the precise position control of manipulator joint. Simulation experiments show that the response time in manipulator joint control system by the SMC method based on GA is reduced 0.62s than the ordinary SMC algorithm. And the system restore stability time with a load change is also reduced 0.7s. External disturbance has no significant effect on the control system. The chattering of controller output is significantly reduced.
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Ge, Xiangyu, Jingzhe Wang, Jianli Ding, et al. "Combining UAV-based hyperspectral imagery and machine learning algorithms for soil moisture content monitoring." PeerJ 7 (May 3, 2019): e6926. http://dx.doi.org/10.7717/peerj.6926.
Texte intégralRésumé :
Soil moisture content (SMC) is an important factor that affects agricultural development in arid regions. Compared with the space-borne remote sensing system, the unmanned aerial vehicle (UAV) has been widely used because of its stronger controllability and higher resolution. It also provides a more convenient method for monitoring SMC than normal measurement methods that includes field sampling and oven-drying techniques. However, research based on UAV hyperspectral data has not yet formed a standard procedure in arid regions. Therefore, a universal processing scheme is required. We hypothesized that combining pretreatments of UAV hyperspectral imagery under optimal indices and a set of field observations within a machine learning framework will yield a highly accurate estimate of SMC. Optimal 2D spectral indices act as indispensable variables and allow us to characterize a model’s SMC performance and spatial distribution. For this purpose, we used hyperspectral imagery and a total of 70 topsoil samples (0–10 cm) from the farmland (2.5 × 104 m2) of Fukang City, Xinjiang Uygur AutonomousRegion, China. The random forest (RF) method and extreme learning machine (ELM) were used to estimate the SMC using six methods of pretreatments combined with four optimal spectral indices. The validation accuracy of the estimated method clearly increased compared with that of linear models. The combination of pretreatments and indices by our assessment effectively eliminated the interference and the noises. Comparing two machine learning algorithms showed that the RF models were superior to the ELM models, and the best model was PIR (R2val = 0.907, RMSEP = 1.477, and RPD = 3.396). The SMC map predicted via the best scheme was highly similar to the SMC map measured. We conclude that combining preprocessed spectral indices and machine learning algorithms allows estimation of SMC with high accuracy (R2val = 0.907) via UAV hyperspectral imagery on a regional scale. Ultimately, our program might improve management and conservation strategies for agroecosystem systems in arid regions.
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Li, Bin, Jiahao Zhu, Ranran Zhou, and Guoxing Wen. "Adaptive Neural Network Sliding Mode Control for a Class of SISO Nonlinear Systems." Mathematics 10, no. 7 (2022): 1182. http://dx.doi.org/10.3390/math10071182.
Texte intégralRésumé :
In this article, a sliding mode control (SMC) is proposed on the basis of an adaptive neural network (NN) for a class of Single-Input–Single-Output (SISO) nonlinear systems containing unknown dynamic functions. Since the control objective is to steer the system states to track the given reference signals, the SMC method is considered by employing the adaptive neural network (NN) strategy for dealing with the unknown dynamic problem. In order to compress the impaction coming from chattering phenomenon (which inherently exists in most SMC methods because of the discontinuous switching term), the boundary layer technique is considered. The basic design idea is to introduce a continuous proportional function to replace the discontinuous switching control term inside the boundary layer so that the chattering can be effectively alleviated. Finally, both Lyapunov theoretical analysis and computer numerical simulation are used to verify the effectiveness of the proposed SMC method.
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Huang, Jiacai, Hongsheng Li, YangQuan Chen, and Qinghong Xu. "Robust Position Control of PMSM Using Fractional-Order Sliding Mode Controller." Abstract and Applied Analysis 2012 (2012): 1–33. http://dx.doi.org/10.1155/2012/512703.
Texte intégralRésumé :
A new robust fractional-order sliding mode controller (FOSMC) is proposed for the position control of a permanent magnet synchronous motor (PMSM). The sliding mode controller (SMC), which is insensitive to uncertainties and load disturbances, is studied widely in the application of PMSM drive. In the existing SMC method, the sliding surface is usually designed based on the integer-order integration or differentiation of the state variables, while in this proposed robust FOSMC algorithm, the sliding surface is designed based on the fractional-order calculus of the state variables. In fact, the conventional SMC method can be seen as a special case of the proposed FOSMC method. The performance and robustness of the proposed method are analyzed and tested for nonlinear load torque disturbances, and simulation results show that the proposed algorithm is more robust and effective than the conventional SMC method.
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Liu, Chengcheng, Gang Lei, Bo Ma, Youguang Guo, and Jianguo Zhu. "Robust Design of a Low-Cost Permanent Magnet Motor with Soft Magnetic Composite Cores Considering the Manufacturing Process and Tolerances." Energies 11, no. 8 (2018): 2025. http://dx.doi.org/10.3390/en11082025.
Texte intégralRésumé :
This paper uses the Taguchi method to optimize the manufacturing process and robust design of a low-cost permanent magnet motor with soft magnetic composite (SMC) cores. For the manufacturing process, SMC cores are produced by using the molding technology without any wire cutting costs. To maximize the relative permeability and minimize the core loss, the Taguchi method is employed to identify the best control factor values for the heat treatment of SMC cores based on a series of experimental results. Due to the manufacturing tolerances, there are significant uncertainties in the core densities and motor dimensions, which will result in big performance variations for the SMC motors in the batch production. To obtain a robust design less sensitive to these tolerances, the conventional Taguchi parameter design method and a sequential Taguchi optimization method are presented to maximize the average torque and minimize the core loss of a low-cost PM motor. Through comparison, it is found that the proposed optimization method is efficient. It can provide an optimal design with better motor performance and manufacturing quality. The proposed method will benefit the industrial production of cost-effective PM-SMC motors with robust and compact designs.
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Du, Mingcheng, Jianyun Zhang, Amgad Elmahdi, et al. "Variation Characteristics and Influencing Factors of Soil Moisture Content in the Lime Concretion Black Soil Region in Northern Anhui." Water 13, no. 16 (2021): 2251. http://dx.doi.org/10.3390/w13162251.
Texte intégralRésumé :
Soil moisture content (SMC) is an important factor affecting crop growth. Based on the field SMC data measured at the Wudaogou experimental station from 1989 to 2019, two typical crop types, wheat and maize, were selected. By combining the groundwater depth, crop growth period, and meteorological factors in the same period, and using classical statistics and redundant analysis (RDA) methods, the characteristics and influencing factors of SMC changes in vertical profiles of different crops were compared and analyzed. The results showed that the SMC and average daily water storage of wheat were greater than that of maize. The crop growth mainly consumed 0–60 cm SMC. The SMC in this area was moderately variable; the SMC of 0–30 cm belongs to the active layer, and the SMC of 30–100 cm belongs to the sub-active layer. The RDA method identified ground temperature, groundwater depth, relative humidity, and the wheat growing period as the main factors affecting soil moisture variation in wheat fields; groundwater depth, relative humidity, and water vapor pressure differences were the main factors affecting soil moisture variation in maize fields. The results can provide a basis for accurate prediction of soil water dynamics and thus provide a reference for irrigation decision-makers.
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Sato, Hayaho, Akito Maruo, and Hajime Igarashi. "Analysis of nonlinear magnetic properties of soft magnetic composite using 2D and 3D discrete element methods." International Journal of Applied Electromagnetics and Mechanics 64, no. 1-4 (2020): 483–92. http://dx.doi.org/10.3233/jae-209355.
Texte intégralRésumé :
This paper presents the three-dimensional modeling of soft magnetic composite (SMC) based on the discrete element method. The proposed method makes it possible to take the possible contact among the magnetic particles in SMC as well as the distributed particle size into consideration. Based on this modeling, the macroscopic B-H characteristics is computed with the finite element method considering magnetic saturation. It is shown that the three-dimensional model of SMC can have larger initial permeability in comparison with the two-dimensional model even if they have the same filling factor.
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Zhang, Bing, Kang Nie, Xinglong Chen, and Yao Mao. "Development of Sliding Mode Controller Based on Internal Model Controller for Higher Precision Electro-Optical Tracking System." Actuators 11, no. 1 (2022): 16. http://dx.doi.org/10.3390/act11010016.
Texte intégralRésumé :
The electro-optical tracking system (ETS) on moving platforms is affected by the vibration of the moving carrier, the wind resistance torque in motion, the uncertainty of mechanisms and the nonlinear friction between frames and other disturbances, which may lead to the instability of the electro-optical tracking platform. Sliding mode control (SMC) has strong robustness to system disturbances and unknown dynamic external signals, which can enhance the disturbance suppression ability of ETSs. However, the strong robustness of SMC requires greater switching gain, which causes serious chattering. At the same time, the tracking accuracy of SMC has room for further improvement. Therefore, in order to solve the chattering problem of SMC and improve the tracking accuracy of SMC, an SMC controller based on internal model control (IMC) is proposed. Compared with traditional SMC, the proposed method can be used to suppress the strongest disturbance with the smallest switching gain, effectively solving the chattering problem of the SMC, while improving the tracking accuracy of the system. In addition, to reduce the adverse influence of sensor noise on the control effect, lifting wavelet threshold de-noising is introduced into the control structure to further improve the tracking accuracy of the system. The simulation and experimental results verify the superiority of the proposed control method.
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Wang, Zhen. "Synchronization of an Uncertain Fractional-Order Chaotic System via Backstepping Sliding Mode Control." Discrete Dynamics in Nature and Society 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/732503.
Texte intégralRésumé :
Backstepping control approach combined with sliding mode control (SMC) technique is utilized to realize synchronization of uncertain fractional-order strict-feedback chaotic system. A backstepping SMC method is presented to compensate the uncertainty which occurs in the slave system. Moreover, the newly proposed control scheme is applied to implement synchronization of fractional-order Duffing-Holmes system. The simulation results demonstrate that the backstepping SMC method is robust against the modeling uncertainties and external disturbances.
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Fazilat, Mehdi, and Nadjet Zioui. "Quantum-Inspired Sliding-Mode Control to Enhance the Precision and Energy Efficiency of an Articulated Industrial Robotic Arm." Robotics 14, no. 2 (2025): 14. https://doi.org/10.3390/robotics14020014.
Texte intégralRésumé :
Maintaining precise and robust control in robotic systems, particularly those with nonlinear dynamics and external disturbances, is a significant challenge in robotics. Sliding-mode control (SMC) is a widely used technique to tackle these issues; however, it is plagued by chattering and computational complexity, which limit its effectiveness in high-precision environments. This study aims to develop and assess a quantum-inspired sliding-mode control (QSMC) strategy to enhance the SMC’s robustness, precision, and computational efficiency, specifically in controlling a six-jointed articulated robotic arm. The methodology involves creating a comprehensive kinematic and dynamic model of the robot, followed by implementing both classic SMC and the proposed Q-SMC in a comparative way. The simulation results confirm that the Q-SMC method outperforms the classic SMC, particularly in reducing chattering, improving tracking accuracy, and decreasing energy consumption by approximately 3.79%. These findings suggest that the Q-SMC technique provides a promising alternative to classical control methods, with potential applications in tasks requiring high precision and efficient robotic manipulations.
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Alnami, Hashim, Sultan H. Hakmi, Saad A. Mohamed Abdelwahab, et al. "Enhanced Adaptive Dynamic Surface Sliding Mode Control for Optimal Performance of Grid-Connected Photovoltaic Systems." Sustainability 16, no. 13 (2024): 5590. http://dx.doi.org/10.3390/su16135590.
Texte intégralRésumé :
This study presents an enhanced, adaptive, and dynamic surface sliding mode control (SMC), a cutting-edge method for improving grid-connected photovoltaic (PV) system performance. The suggested control approach uses dynamic SMC and adaptive approaches to enhance the robustness and efficiency of a system. Proportional–integral (PI) and SMC, two control systems for maximum power point tracking (MPPT) in PV systems, are compared in this paper. This study finds that the SMC system is a more effective and efficient MPPT approach for PV systems compared to the conventional PI control system. The SMC system’s unique feature is the capacity to stabilize grid voltage and attain a modulation index of less than one. An important component of power electronic system control is the index, which acts as a parameter representing the relationship between the output signal’s amplitude and the reference signal’s amplitude. The SMC method demonstrates improved robustness, efficiency, and stability, especially in dynamic operating settings with load and solar radiation changes. Compared to the PI control, the SMC exhibits a noteworthy 75% reduction in voltage fluctuations and an improvement in the power output of 5% to 10%. Regarding output power optimization, voltage stability, and accurate current tracking, the SMC system performs better than the PI control system. Furthermore, the SMC technique maintains a modulation index below one and guarantees grid voltage stability, both of which are essential for the efficiency and stability of power electrical systems.
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Toni, Tina, David Welch, Natalja Strelkowa, Andreas Ipsen, and Michael P. H. Stumpf. "Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems." Journal of The Royal Society Interface 6, no. 31 (2008): 187–202. http://dx.doi.org/10.1098/rsif.2008.0172.
Texte intégralRésumé :
Approximate Bayesian computation (ABC) methods can be used to evaluate posterior distributions without having to calculate likelihoods. In this paper, we discuss and apply an ABC method based on sequential Monte Carlo (SMC) to estimate parameters of dynamical models. We show that ABC SMC provides information about the inferability of parameters and model sensitivity to changes in parameters, and tends to perform better than other ABC approaches. The algorithm is applied to several well-known biological systems, for which parameters and their credible intervals are inferred. Moreover, we develop ABC SMC as a tool for model selection; given a range of different mathematical descriptions, ABC SMC is able to choose the best model using the standard Bayesian model selection apparatus.
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Tian, Miao Miao, Chao Yang Guo, Jin Yan, and Ya Fei Li. "Mix Design Method of the SMC Cold Temperature Modified Asphalt Mixture." Key Engineering Materials 744 (July 2017): 185–89. http://dx.doi.org/10.4028/www.scientific.net/kem.744.185.
Texte intégralRésumé :
The SMC cold temperature asphalt mixture consumed less energy and harmful emission compares with the traditional HMA and WMA, and it can be worked at the subzero temperature or after a long time storage, which makes the construction and maintenance of the asphalt pavement in a special environment (low temperature) and special conditions (without a hot mix station) come true. It has been widely used in Beijing, Xinjiang, Sichuan, Tibet, etc. with a satisfied performance. Highway construction and maintenance technology level of China would be positively promoted by using the SMC asphalt mixtures.
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Neupane, Kuldip. "Leadership and Management Trait of SMC Members in School Governance." Siddhajyoti Interdisciplinary Journal 4, no. 1 (2023): 69–80. http://dx.doi.org/10.3126/sij.v4i1.54135.
Texte intégralRésumé :
Among various school governing bodies, the School Management Committee (SMC) is the leading one that designs the vision and missions for the school. Nepalese education policy has given SMC the duty of school improvement. The theory of governance explains leadership and management quality in its process. So, SMC, from the viewpoint of governance theory, better performs when possesses leadership and management knowledge. This mixed method research explored these qualities in the SMC of Kanchanjunga Secondary School. The qualities are explored from the viewpoints of students and the SMC chair both, where the quantitative data were collected from the students and qualitative from the SMC chair. The research found that the SMC of the researched school possessed less leadership and management qualities. The SMC members need knowledge and training on the traits of leadership and management like decision making and dissemination, setting goals for the school, participatory approach in decision making and implementation, communicative approach, transparency, and accountability
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Islam, Shafiqul, and Peter X. Liu. "Output feedback sliding mode control for robot manipulators." Robotica 28, no. 7 (2010): 975–87. http://dx.doi.org/10.1017/s0263574709990816.
Texte intégralRésumé :
SUMMARYIn this work, we propose an output feedback sliding mode control (SMC) method for trajectory tracking of robotic manipulators. The design process has two steps. First, we design a stable SMC controller by assuming that all state variables are available. Then, an output feedback version of this SMC design is presented, which incorporates a model-free linear observer to estimate unknown velocity signals. We then show that the tracking performance under the output feedback design can asymptotically converge to the performance achieved under state-feedback-based SMC design. A detailed stability analysis is given, which shows semi-global uniform ultimate boundedness property of all the closed-loop signals. The proposed method is implemented and evaluated on a robotic system to illustrate the effectiveness of the theoretical development.
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Huang, Jie, and Gang Li. "An Expansion Method of Reliable Data Transmission of the Short-Message Communication on Satellite Network." Advanced Engineering Forum 4 (June 2012): 3–8. http://dx.doi.org/10.4028/www.scientific.net/aef.4.3.
Texte intégralRésumé :
Short-message communication mechanism is one of the most frequently methods used on the field of satellite data transmission. Under the existing satellite network, we provide an expansion method of reliable data transmission of short message communication named EMRDT-SMC, which solves negative compression problem of transmission capacity expansion when the amount of short message is below normal, and also solves reliable data transmission problem while satellite microwave transmission causes short message loss. Based on the measurement over a small test-bed, it shows that the method EMRDT-SMC can obtain the better network performance.
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Mehedi, Fayçal, Rachid Taleb, Abdelkadir Belhadj Djilali, and Adil Yahdou. "SMC based DTC-SVM control of five-phase permanent magnet synchronous motor drive." Indonesian Journal of Electrical Engineering and Computer Science 20, no. 1 (2020): 100. http://dx.doi.org/10.11591/ijeecs.v20.i1.pp100-108.
Texte intégralRésumé :
<span>This article presents an improved Direct Torque Control (DTC) technique with space vector modulation (SVM) for a five-phase permanent magnet synchronous motor (PMSM) using a sliding mode speed control (SMC).The proposed control scheme of the five-phase PMSM combines the advantages of SMC control and the SVM algorithm. The SMC method insensitive to uncertainties, in particular external disturbances and parameter variations. In this paper, the SMC controller is used to control the rotor speed of the five-phase PMSM based on DTC-SVM. The rotor speed response, torque and stator flux are determined and compared with traditional control method. The simulations results confirm the validity and effectiveness of the proposed control technique in terms of performance and robustness against machine parameter variations (inertia variation). The efficiency of the proposed method applied on the five-phase PMSM is verified by the MATLAB/Simulink.</span>
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Fayçal, Mehedi Rachid Taleb, Belhadj Djilali Abdelkadir, and Yahdou Adil. "SMC based DTC-SVM control of five-phase permanent magnet synchronous motor drive." Indonesian Journal of Electrical Engineering and Computer Science 20, no. 1 (2020): 100–108. https://doi.org/10.11591/ijeecs.v20.i1.pp100-108.
Texte intégralRésumé :
This article presents an improved Direct Torque Control (DTC) technique with space vector modulation (SVM) for a five-phase permanent magnet synchronous motor (PMSM) using a sliding mode speed control (SMC). The proposed control scheme of the five-phase PMSM combines the advantages of SMC control and the SVM algorithm. The SMC method insensitive to uncertainties, in particular external disturbances and parameter variations. In this paper, the SMC controller is used to control the rotor speed of the five-phase PMSM based on DTC-SVM. The rotor speed response, torque and stator flux are determined and compared with traditional control method. The simulations results confirm the validity and effectiveness of the proposed control technique in terms of performance and robustness against machine parameter variations (inertia variation). The efficiency of the proposed method applied on the five-phase PMSM is verified by the MATLAB/Simulink.
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Chung, Jin Hyun, Hye Ryeon Lim, Tek Hyung Lee, et al. "Growth of Smooth Muscle Cell and Endothelial Cell on PLGA Film Containing EGCG." Key Engineering Materials 342-343 (July 2007): 93–96. http://dx.doi.org/10.4028/www.scientific.net/kem.342-343.93.
Texte intégralRésumé :
Poly (D,L-latic-co-glycolic acid) (PLGA) has been used as the artificial scaffold for blood vessel formation. In order to hinder smooth muscle cell (SMC) angiogenesis, new scaffold design method of loading Epigallocatechin 3-O-gallate (EGCG) on PLGA film was introduced. PLGA and EGCG were dissolved in acetone and film-shape scaffold was manufactured. Antiangiogenetic effect of EGCG released on scaffold was analyzed for SMC and human umbilical vein endothelial cell (HUVEC) and method for selective inhibition from the difference of growth of SMC and HUVEC was suggested.
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Bonfig, Teresa, Simon Wehler, and Lothar Kroll. "Radar sensor integration and quality testing of sheet moulding compound parts in the automotive frequency range." Technologies for Lightweight Structures (TLS) 5, no. 1 (2022): 123–30. http://dx.doi.org/10.21935/tls.v5i1.167.
Texte intégralRésumé :
Sheet moulding compounds (SMC), a type of fiber-reinforced polymers with discontinuous fibers, are a highly used lightweight material due to their cost efficiency and processability. Since the use of radar sensors behind structural skin body parts for advanced drivers assistant systems in the automobile industry is increasing, the usability of this kind of material as a radar cover is examined. Additionally, a method for the analysis of SMC parts with radar measurement methods in the Gigahertz area is introduced. The hereby considered parameters are the fiber orientation, fiber volume content, and quality failures like welding lines as they are crucial for the mechanical properties of the material. The methods presented are already in use in the automotive industry for quality assurance of radar covers and show potential as a fast and non-destructive method to analyse those important material parameters of SMC components.
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Ali, Hazem, Azhar Jabbar Abdulridha, Rawaa Khaleel, and Kareem Kareem A. Hussein. "LQR/Sliding Mode Controller Design Using Particle Swarm Optimization for Crane System." Al-Nahrain Journal for Engineering Sciences 23, no. 1 (2020): 45–50. http://dx.doi.org/10.29194/njes.23010045.
Texte intégralRésumé :
In this work, the design procedure of a hybrid robust controller for crane system is presented. The proposed hybrid controller combines the linear quadratic regulator (LQR) properties with the sliding mode control (SMC) to obtain an optimal and robust LQR/SMC controller. The crane system which is represented by pendulum and cart is used to verify the effectiveness of the proposed controller. The crane system is considered one of the highly nonlinear and uncertain systems in addition to the under-actuating properties. The parameters of the proposed LQR/SMC are selected using Particle Swarm Optimization (PSO) method. The results show that the proposed LQR/SMC controller can achieve a better performance if only SMC controller is used. The robustness of the proposed controller is examined by considering a variation in system parameters with applying an external disturbance input. Finally, the superiority of the proposed LQR/SMC controller over the SMC controller is shown in this work.
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Eddine, Kerrouche Kamel Djamel, Wang Lina, Seddjar Abderrahmane, Bensaada Messaoud, Pedro Henrique de Oliveira Nogueira, and Kerrouche Mustapha Boualem. "Comprehensive Analysis and Design of Electrical Power Systems for Nanosatellite Platforms: A Focus on Robust MPPT Control Using Sliding Mode Control Method." International Journal of Energy Research 2024 (April 17, 2024): 1–32. http://dx.doi.org/10.1155/2024/4879696.
Texte intégralRésumé :
This paper is aimed at performing a comprehensive review of the approaches employed in nanosatellite platforms, specifically 1 U and 3 U, for electrical power systems (EPS). Moreover, it seeks to develop a robust maximum power point tracking (MPPT) controller using the sliding mode control (SMC) method. The proposed control strategy is intended to monitor the solar panel’s maximum power point (MPP) and adapt to changes in temperatures and solar irradiance in low Earth orbit (LEO). The EPS model, designed with the proposed sizing method, is built in MATLAB-Simulink and integrates a solar panel, battery storage, and power converters controlled by diverse MPPT methods. Then, simulation results demonstrate the effectiveness of the proposed SMC approach compared to other conventional control methods for the designed EPS under varying LEO conditions. To achieve a robust validation of the most appropriate MPPT control method under steady-state conditions, this paper presents an experimental investigation into the proposed EPS hardware design. The proposed SMC method achieved an increase in power generation from 10% to 12% for buck and boost power converters, respectively, compared to traditional control methods.
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Köse, Ercan, and Aydın Mühürcü. "Comparative Controlling of the Lorenz Chaotic System Using the SMC and APP Methods." Mathematical Problems in Engineering 2018 (December 6, 2018): 1–9. http://dx.doi.org/10.1155/2018/9612749.
Texte intégralRésumé :
The Lorenz chaotic system is based on a nonlinear behavior and this causes the system to be unstable. Therefore, two different controller models were developed and named as the adaptive pole placement and sliding mode control (SMC) methods for the establishment of continuous time nonlinear Lorenz chaotic system. In order to achieve this, an improved controller structure was developed first theoretically for both the controller methods and then tested practically using the numerical samples. During the establishment of adaptive pole placement method for the Lorenz chaotic system, various stages were applied. The nonlinear chaotic system was also linearized by means of Taylor Series expansion processes. In addition, the feedback matrix of the adaptive pole placement method was determined using linear Jacobian matrix. The chaotic system reached an equilibrium point by using both the SMC and adaptive pole placement methods; however the simulation results of the SMC had better success than adaptive pole placement control technique.
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Govor, G. A., O. F. Demidenko, A. R. Normirzaev, and M. A. Tukhtabayev. "Properties of a composite magnetically soft material based on coated iron powders." E3S Web of Conferences 365 (2023): 05001. http://dx.doi.org/10.1051/e3sconf/202336505001.
Texte intégralRésumé :
A method has been developed to study the properties of composite SMC materials based on high-purity iron powders, the lowest carbon content materials, for example, ABC100.30 iron powder, have higher values of magnetic parameters and minimal losses. The structure and morphology of the surface of the obtained composite materials were studied. The results of the influence on the properties of SMC materials of various insulating coatings were obtained, and SMC materials with titanium oxide coatings had better characteristics. The influence of the thickness of the oxide coating on the decrease in magnetic permeability of SMC materials was studied. The influence of insulating coatings' thickness on the SMC material's magnetic properties was determined.
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Liu, Qixin, Xingfa Gu, Xinran Chen, et al. "Soil Moisture Content Retrieval from Remote Sensing Data by Artificial Neural Network Based on Sample Optimization." Sensors 22, no. 4 (2022): 1611. http://dx.doi.org/10.3390/s22041611.
Texte intégralRésumé :
Soil moisture content (SMC) plays an essential role in geoscience research. The SMC can be retrieved using an artificial neural network (ANN) based on remote sensing data. The quantity and quality of samples for ANN training and testing are two critical factors that affect the SMC retrieving results. This study focused on sample optimization in both quantity and quality. On the one hand, a sparse sample exploitation (SSE) method was developed to solve the problem of sample scarcity, resultant from cloud obstruction in optical images and the malfunction of in situ SMC-measuring instruments. With this method, data typically excluded in conventional approaches can be adequately employed. On the other hand, apart from the basic input parameters commonly discussed in previous studies, a couple of new parameters were optimized to improve the feature description. The Sentinel-1 SAR and Landsat-8 images were adopted to retrieve SMC in the study area in eastern Austria. By the SSE method, the number of available samples increased from 264 to 635 for ANN training and testing, and the retrieval accuracy could be markedly improved. Furthermore, the optimized parameters also improve the inversion effect, and the elevation was the most influential input parameter.
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Li, Limin, Zhaoyang Guo, and Yuliang Lin. "A Design Method of Styreneic Methyl Copolymers Normal Temperature Modified Asphalt Mixture Based on Performance Balance." Materials 15, no. 18 (2022): 6193. http://dx.doi.org/10.3390/ma15186193.
Texte intégralRésumé :
The objective of this research was to develop a solution for the deterioration effect on the high-temperature rutting performance and water stability of SMC. This research proposed a method for designing an SMC normal temperature modified asphalt mixture based on the existing findings, experimental research and the performance balance. First, the power function curve model of the aggregate gradation was put forward. The 0.075 mm, 4.75 mm and nominal maximum particle size were the key points of the aggregate gradation, and their passing rate was about 6%, 30%, and 95% respectively. Then, on the basis of the quadratic curve model, a method for determination of the optimum asphalt aggregate ratio of SMC normal temperature modified asphalt mixture was put forward, considering the skeleton-density structure. Last, rutting tests, small beam bending tests, freeze-thaw split tests, permeability coefficient tests, texture depth tests and pavement roughness tests were conducted, and the test results all met the performance requirements of the specifications for the construction of highway asphalt pavement in China perfectly, especially the high-temperature and water stability properties, which indicated that the design method for SMC normal temperature modified asphalt mixtures based on performance balance presented in this paper was reasonable and practical.
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Dai, Yong, and Duo Wang. "A Tube Model Predictive Control Method for Autonomous Lateral Vehicle Control Based on Sliding Mode Control." Sensors 23, no. 8 (2023): 3844. http://dx.doi.org/10.3390/s23083844.
Texte intégralRésumé :
This paper aims to enhance the lateral path tracking control of autonomous vehicles (AV) in the presence of external disturbances. While AV technology has made significant strides, real-world driving scenarios often pose challenges such as slippery or uneven roads, which can adversely affect the lateral path tracking control and reduce driving safety and efficiency. Conventional control algorithms struggle to address this issue due to their inability to account for unmodeled uncertainties and external disturbances. To tackle this problem, this paper proposes a novel algorithm that combines robust sliding mode control (SMC) and tube model predictive control (MPC). The proposed algorithm leverages the strengths of both MPC and SMC. Specifically, MPC is used to derive the control law for the nominal system to track the desired trajectory. The error system is then employed to minimize the difference between the actual state and the nominal state. Finally, the sliding surface and reaching law of SMC are utilized to derive an auxiliary tube SMC control law, which helps the actual system keep up with the nominal system and achieve robustness. Experimental results demonstrate that the proposed method outperforms conventional tube MPC, linear quadratic regulator (LQR) algorithms, and MPC in terms of robustness and tracking accuracy, especially in the presence of unmodeled uncertainties and external disturbances.
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Truong, Thanh Nguyen, Anh Tuan Vo, Hee-Jun Kang, and Ic-Pyo Hong. "A Novel Model-Free Nonsingular Fixed-Time Sliding Mode Control Method for Robotic Arm Systems." Mathematics 13, no. 10 (2025): 1579. https://doi.org/10.3390/math13101579.
Texte intégralRésumé :
This paper introduces a novel model-free nonsingular fixed-time sliding mode control (MF-NFxTSMC) strategy for precise trajectory tracking in robot arm systems. Unlike conventional sliding mode control (SMC) approaches that require accurate dynamic models, the proposed method leverages the time delay estimation (TDE) approach to effectively estimate system dynamics and external disturbances in real-time, enabling a fully model-free control solution. This significantly enhances its practicality in real-world scenarios where obtaining precise models is challenging or infeasible. A significant innovation of this work lies in designing a novel fixed-time control framework that achieves faster convergence than traditional fixed-time methods. Building on this, a novel MF-NFxTSMC law is developed, featuring a novel singularity-free fixed-time sliding surface (SF-FxTSS) and a novel fixed-time reaching law (FxTRL). The proposed SF-FxTSS incorporates a dynamic proportional term and an adaptive exponent, ensuring rapid convergence and robust tracking. Notably, its smooth transition between nonlinear and linear dynamics eliminates the singularities often encountered in terminal and fixed-time sliding mode surfaces. Additionally, the designed FxTRL effectively suppresses chattering while guaranteeing fixed-time convergence, leading to smoother control actions and reduced mechanical stress on the robotic hardware. The fixed-time stability of the proposed method is rigorously proven using the Lyapunov theory. Numerical simulations on the SAMSUNG FARA AT2 robotic platform demonstrate the superior performance of the proposed method in terms of tracking accuracy, convergence speed, and control smoothness compared to existing strategies, including conventional SMC, finite-time SMC, approximate fixed-time SMC, and global fixed-time nonsingular terminal SMC (NTSMC). Overall, this approach offers compelling advantages, i.e., model-free implementation, fixed-time convergence, singularity avoidance, and reduced chattering, making it a practical and scalable solution for high-performance control in uncertain robotic systems.
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Liu, Zhenhua, Li Zhao, Yiping Peng, Guangxing Wang, and Yueming Hu. "Improving Estimation of Soil Moisture Content Using a Modified Soil Thermal Inertia Model." Remote Sensing 12, no. 11 (2020): 1719. http://dx.doi.org/10.3390/rs12111719.
Texte intégralRésumé :
There has been substantial research for estimating and mapping soil moisture content (SMC) of large areas using remotely sensed images by developing models of soil thermal inertia (STI). However, it is still a great challenge to accurately estimate SMC because of the impact of vegetation canopies and vegetation-induced shadows in mixed pixels on the estimates. In this study, a new method was developed to increase the estimation accuracy of SMC for an irrigated area located in YingKe of Heihe, China, using ASTER data. In the method, an original model of estimating bare STI was modified by decomposing a mixed pixel into three components, bare soil, vegetated soil, and shaded soil, as well as extracting their fractions using a spectral unmixing analysis and then deriving their fluxes. Moreover, the 90 m spatial resolution thermal images were scaled down to the 15 m spatial resolution by data fusion of a discrete wavelet transform (DWT) and re-sampling using the nearest neighbor method (NNM). The modified model was compared with the original model based on the mean absolute error (MAE) and relative root mean square error (RRMSE) between the SMC estimates and observations from 30 validation soil samples. The results indicated that compared to the original model based on the parallel dual layer, the modified STI model based on the serial dual layer statistically significantly decreased the MAE and RRMSE of the SMC estimates by 63.0–63.2% and 63.0–63.5%, respectively. The 15 m spatial resolution thermal bands obtained by the DWT data fusion provided more detailed information of SMC but did not significantly improve its estimation accuracy than the 15 m spatial resolution thermal bands by re-sampling using NNM. This implied that the novel method offered insights on how to increase the accuracy of retrieving SMC estimates in vegetated areas.