Journal articles: 'Fuzzy boundary layer'

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Smith, Elizabeth N., and Jacob T. Carlin. "A multi-instrument fuzzy logic boundary-layer-top detection algorithm." Atmospheric Measurement Techniques 17, no. 13 (2024): 4087–107. http://dx.doi.org/10.5194/amt-17-4087-2024.

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Abstract. Understanding the boundary-layer height and its dynamics is crucial for a wide array of applications spanning various fields. Accurate identification of the boundary-layer top contributes to improved air quality predictions, pollutant transport assessments, and enhanced numerical weather prediction through parameterization and assimilation techniques. Despite its significance, defining and observing the boundary-layer top remain challenging. Existing methods of estimating the boundary-layer height encompass radiosonde-based methods, radar-based retrievals, and more. As emerging boundary-layer observation platforms emerge, it is useful to reevaluate the efficacy of existing boundary-layer-top detection methods and explore new ones. This study introduces a fuzzy logic algorithm that leverages the synergy of multiple remote sensing boundary-layer profiling instruments: a Doppler lidar, infrared spectrometer, and microwave radiometer. By harnessing the distinct advantages of each sensing platform, the proposed method enables accurate boundary-layer height estimation both during daytime and nocturnal conditions. The algorithm is benchmarked against radiosonde-derived boundary-layer-top estimates obtained from balloon launches across diverse locations in Wisconsin, Oklahoma, and Louisiana during summer and fall. The findings reveal notable similarities between the results produced by the proposed fuzzy logic algorithm and traditional radiosonde-based approaches. However, this study delves into the nuanced differences in their behavior, providing insightful analyses about the underlying causes of the observed discrepancies. While developed with the three instruments mentioned above, the fuzzy logic boundary-layer-top detection algorithm, called BLISS-FL, could be adapted for other wind and thermodynamic profilers. BLISS-FL is released publicly, fostering collaboration and advancement within the research community.

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Lee, Heejin, Dong-Yon Kim, Taeck-Kie Lee, Sang-Hoon Kim, and Mignon Park. "Tracking Control of Variable Structure Using Fuzzy Variable Boundary Layer." Journal of Advanced Computational Intelligence and Intelligent Informatics 3, no. 4 (1999): 332–38. http://dx.doi.org/10.20965/jaciii.1999.p0332.

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Control gain greatly affects variable structure system (VSS) performance as a system design parameter. The thin boundary layer used to eliminate chatter neighbors the sliding surface. Sliding control based on a variable boundary layer tracks better than a fixed layer. We propose variable structure control using fuzzy algorithms in control gain and the boundary layer to increase tracking efficiency, proving its feasibility in application to a simple nonlinear system.

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Bianco, Laura, James M. Wilczak, and Allen B. White. "Convective Boundary Layer Depth Estimation from Wind Profilers: Statistical Comparison between an Automated Algorithm and Expert Estimations." Journal of Atmospheric and Oceanic Technology 25, no. 8 (2008): 1397–413. http://dx.doi.org/10.1175/2008jtecha981.1.

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Abstract A previous study showed success in determining the convective boundary layer depth with radar wind-profiling radars using fuzzy logic methods, and improvements to the earlier work are discussed. The improved method uses the Vaisala multipeak picking (MPP) procedure to identify the atmospheric signal in radar spectra in place of a fuzzy logic peak picking procedure that was previously used. The method then applies fuzzy logic techniques to calculate the depth of the convective boundary layer. The planetary boundary layer depth algorithm is improved with respect to the one used in the previous study in that it adds information obtained from the small-scale turbulence (vertical profiles of the spectral width of the vertical velocity), while also still using vertical profiles of the radar-derived refractive index structure parameter C2n and the variance of vertical velocity. Modifications to the fuzzy logic rules (especially to those using vertical velocity data) that improve the algorithm’s accuracy in cloudy boundary layers are incorporated. In addition, a reliability threshold value to the fuzzy logic–derived score is applied to eliminate PBL depth data values with low score values. These low score values correspond to periods when the PBL structure does not match the conceptual model of the convective PBL built into the algorithm. Also, as a final step, an optional temporal continuity test on boundary layer depth has been developed that helps improve the algorithm’s skill. A comparison with independent boundary layer depth estimations made “by eye” by meteorologists at two radar wind-profiler sites, significantly different in their characteristics, shows that the new improved method gives significantly more accurate estimates of the boundary layer depth than does the previous method, and also much better estimates than the simpler “standard” method of selecting the peak of C2n. The new method produces an absolute error of the mixing-depth estimates comparable to the vertical range resolution of the profilers.

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Lu, Hua Cai, Juan Ti, Yi Ming Yuan, and Li Sheng Wei. "Sensorless Control for PMLSM Based on Fuzzy Sliding Mode Observer." Applied Mechanics and Materials 556-562 (May 2014): 2270–73. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.2270.

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In this paper, a new sensorless control method is proposed for a permanent magnet linear synchronous motor based on Fuzzy sliding mode observer, which combines the advantages of sliding mode observer and Fuzzy controller respectively. The difference between the current estimated value and the actual current value is regarded as sliding mode function; sliding mode function (current error) and variation of the error are used as the input of fuzzy controller, and the width of the boundary layer as the output, adjusting the width of the boundary layer dynamically in real time. The simulation results show that Fuzzy sliding mode observer is able to find a balance between soft chattering and steady-state error, keep the system robustness and control precision.

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Zhang, Xiaoyu. "Sliding Mode-Like Fuzzy Logic Control With Adaptive Boundary Layer for Multiple-Variable Discrete Nonlinear Systems." Journal of Intelligent Systems 25, no. 2 (2016): 209–20. http://dx.doi.org/10.1515/jisys-2015-0019.

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AbstractMore serious chattering emerges in discrete systems of sliding mode control. The paper presents a sliding mode-like fuzzy logic control design, which eliminates the chattering, for a class of discrete nonlinear systems with multiple variables. First, the boundary layer is self-tuned on-line, and then, the chattering free is obtained. Consequently, the fuzzy logic control (FLC) is designed to approximate the sliding mode control (SMC) with boundary layer self-tuning. Finally, the performance of the robustness, chattering free, and adaption are verified by the simulation results.

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Yang, Jie, Tian Luo, Fan Zhao, Shuai Li, and Wei Zhou. "Fuzzy Knowledge Distance with Three-Layer Perspectives in Neighborhood System." Mathematical Problems in Engineering 2021 (May 22, 2021): 1–15. http://dx.doi.org/10.1155/2021/9977488.

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Information granule is the basic element in granular computing (GrC), and it can be obtained according to the granulation criterion. In neighborhood rough sets, current uncertainty measures focus on computing the knowledge granulation of single granular space and have two main limitations: (i) neglecting the structural information of boundary regions and (ii) the inability to reflect the difference between neighborhood granular spaces with the same uncertainty for approximating a target concept. Firstly, a fuzziness-based uncertainty measure for neighborhood rough sets is introduced to characterize the structural information of boundary regions. Moreover, from the perspective of distance, based on the idea of density peaks, we present a fuzzy-neighborhood-granule-distance- (FNGD-) based method to discover the relationship between granules in a granular space. Then, to characterize the difference between granular spaces for approximating a target concept, we present the fuzzy neighborhood granular space distance (FNGSD) and fuzzy neighborhood boundary region distance (FNBRD). FNGD, FNGSD, and FNBRD are hierarchically organized from fineness to coarseness according to the semantics of granularity, which provide three-layer perspectives in the neighborhood system.

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Lee, Heejin, Euntai Kim, Hyung-Jin Kang, and Mignon Park. "A new sliding-mode control with fuzzy boundary layer." Fuzzy Sets and Systems 120, no. 1 (2001): 135–43. http://dx.doi.org/10.1016/s0165-0114(99)00072-x.

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Tu, K. Y., T. T. Lee, and C. H. Wang. "Design of a New Fuzzy Suction Controller Using Fuzzy Modeling for Nonlinear Boundary Layer." IEEE Transactions on Fuzzy Systems 13, no. 5 (2005): 605–16. http://dx.doi.org/10.1109/tfuzz.2005.856564.

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Jiang, Shan, Wenhao Feng, Peng Zheng, Jun Liu, and Jun Yang. "Pneumatic position servo control of magnetic resonance compatible needle insertion robot." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 227, no. 7 (2012): 1469–80. http://dx.doi.org/10.1177/0954406212460972.

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This paper presents a control methodology that enables nonlinear model-base control of pulse width modulated (PWM) pneumatic position servo control system of a magnetic resonance (MR) compatible needle insertion robot used for MRI-guided prostate brachytherapy. Sliding mode control with a boundary layer is investigated based on the equivalent continuous-time dynamic model. Considering chattering in sliding mode control applications, especially in motion control of the robot, a fuzzy method is developed to tune the boundary layer of the sliding mode controller. Simulation and experimental results indicate that the controller is effective in both position control and trajectory tracking. With the boundary layer increasing, the steady state error of the response is becoming larger; however the maximum error is less than 0.2 mm. This steady state performance meets the accuracy requirement.

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J. Nirmala. "A New Inventive Approach to Nano Fuzzy Soft Topological Space Using Mathematical Analysis." Communications on Applied Nonlinear Analysis 31, no. 8s (2024): 747–56. http://dx.doi.org/10.52783/cana.v31.1586.

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The important theme of this paper is to define a lower and upper approximation for the set under consideration in order to examine a novel class of topological field known as Nano fuzzy soft topological space. Fuzzy topology coverts ordered structure to topological structure by using by its own criteria conditions. Nano topology is defined with the help of equivalence relation so that even micro spacing is included in the topological space. The condition of these two topological space has been merged and a new space known as Nano fuzzy topological space has been investigated and studied. Soft sets are an abstraction of fuzzy set theory which was interposed to deal with uncertainty conditions using parameters. Using soft sets, Nano fuzzy topology can be extended to a new form called Nano fuzzy soft topological space and it can be used to study matters of vagueness by defining a proper boundary layer. Since this concept depends upon defining appropriate boundary layers using topological concepts, it easy to determine the key components for a particular problem by properly defining three important regions which are upper approximation area, lower approximation area and boundary region. The use of Nano fuzzy soft topological space in predicting the cause of a disease has been discussed in this paper. It can be extended to study any complex problems in real life by converting it to a Nano fuzzy soft topological space using the three main key factors.

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Ju, Peilun, Yongfeng Ju, and Jiacheng Song. "Fuzzy Adaptive Asymptotic Control for a Class of Large-Scale High-Order Unknown Nonlinear Systems." Applied Sciences 13, no. 15 (2023): 8968. http://dx.doi.org/10.3390/app13158968.

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This paper studies the asymptotic control problem of a class of large-scale high-order nonlinear systems (LSHONSs), and an asymptotic fuzzy adaptive dynamic surface controller is developed. Unknown nonlinear terms are learned online by fuzzy logic systems (FLSs) such that the accurate nonlinear model is released in the controller design procedure, where the parameters of FLSs are updated by developing adaptive laws. To compensate for the “boundary error” caused by the dynamic surface control method where a linear filter is added in the backstepping procedure to handle the “explosion of complexity” problem, a nonlinear filter is proposed to eliminate the boundary layer error. Some simulations are given to demonstrate the effectiveness of the proposed algorithm.

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Giap, Van-Nam, and Shyh-Chour Huang. "Effectiveness of fuzzy sliding mode control boundary layer based on uncertainty and disturbance compensator on suspension active magnetic bearing system." Measurement and Control 53, no. 5-6 (2020): 934–42. http://dx.doi.org/10.1177/0020294020905044.

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This paper presents the disturbance and uncertainty suppression by using the nonlinear disturbance observer and an extended state observer for a nonlinear active magnetic bearing system. Otherwise, the chattering free is assured by a fuzzy controller, where the fixed sliding mode surface boundary is regulated by fuzzy boundary layer. The stability of the system is guaranteed by Lyapunov condition. First, the nonlinear disturbance observer is presented to estimate the disturbance from outside of the system. Second, the system parameter variations are estimated by an extended state observer with the construction via the estimated disturbance value. Third, the proportional–integral–derivative sliding mode surface has been constructed due to the chattering values that appear from the high-frequency switching control values. Fourth, these chattering values are reduced by using a Mamdani fuzzy logic control. The proposed control methodology was given by the MATLAB simulation. The overshoot value that is equal to zero, narrow settling time, and the average distance tracking error value which is quite small are archived.

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Gholami, Alireza, and Amir H. D. Markazi. "DIRECT ADAPTIVE FUZZY SLIDING OBSERVATION AND CONTROL." Transactions of the Canadian Society for Mechanical Engineering 36, no. 4 (2012): 329–42. http://dx.doi.org/10.1139/tcsme-2012-0023.

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In this paper, a new direct adaptive fuzzy sliding observation and control (AFSOC) method is proposed. The method can be applied to a class of unknown nonlinear systems. The proposed observer estimates the closed-loop state tracking error asymptotically, provided that the output gain matrix includes Hurwitz coefficients. The chattering phenomenon is overcome by using a boundary layer around the sliding surface. The stability of the AFSOC method is proved using the Lyapunov stability theory. Numerical simulation on a benchmark chaotic system depicts the effectiveness of the proposed algorithm.

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Fan, Duosi, Jinglei Xu, Matthew X. Yao, and Jean-Pierre Hickey. "On the detection of internal interfacial layers in turbulent flows." Journal of Fluid Mechanics 872 (June 7, 2019): 198–217. http://dx.doi.org/10.1017/jfm.2019.343.

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A novel approach to identify internal interfacial layers, or IILs, in wall-bounded turbulent flows is proposed. Using a fuzzy cluster method (FCM) on the streamwise velocity component, a unique and unambiguous grouping of the uniform momentum zones (UMZs) is achieved, thus allowing the identification of the IILs. The approach overcomes some of the key limitations of the histogram-based IIL identification methods. The method is insensitive to the streamwise domain length, can be used on inhomogeneous grids, uses all the available flow field data, is trivially extended to three dimensions and does not need user-defined parameters (e.g. number of bins) other than the number of zones. The number of zones for a given snapshot can be automatically determined by an a priori algorithm based on a kernel density estimation algorithm, or KDE. This automated approach is applied to compute the average number of UMZs as a function of Reynolds number $Re_{\unicode[STIX]{x1D70F}}$ in turbulent channel flows in several numerical simulations. This systematic approach reveals a dependence of the Reynolds number on the average number of UMZs in the channel flow; this supports previously reported observations in the boundary layer. The fuzzy clustering approach is applied to the turbulent boundary layer (experimental, planar particle image velocimetry) and channel flow (numerical, direct numerical simulation) at varying Reynolds numbers. The interfacial layers are characterized by a strong concentration of spanwise vorticity, with the outer-most layer located at the upper edge of the log layer. The three-dimensional interface identification reveals a streak-like organization. The large-scale motion (LSM) at the outer region of the channel flow boundary layer modulates the outer IIL. The corrugations of the outer IIL are aligned with the LSM and the conditional correlation of the inner and outer IIL height shows that extreme near-wall events leave their mark on the outer IIL corrugations.

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Zhang, Youan, Jianming Wei, Hong Wang, and Jingmao Liu. "Adaptive fuzzy iterative learning control of robotic systems with time-delay outputs and input dead zone via observer." Filomat 32, no. 5 (2018): 1571–80. http://dx.doi.org/10.2298/fil1805571z.

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This paper presents an adaptive fuzzy iterative learning control method for the output tracking problem of robotic systems with unknown time delay output and input dead-zone. A state observer is designed to estimate unmeasurable velocity variables. By introducing boundary layer function, the identical initial condition for most iterative learning control schemes is relaxed. By combining appropriate Lyapunov-Krasovskii functional and fuzzy logic systems approximation technique, the proposed control scheme can guarantee that the output tracking converges to the desired reference trajectory within an error tolerance and all the closed-loop signals remain bounded.

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Allabakash, S., P. Yasodha, L. Bianco, S. Venkatramana Reddy, P. Srinivasulu, and S. Lim. "Improved boundary layer height measurement using a fuzzy logic method: Diurnal and seasonal variabilities of the convective boundary layer over a tropical station." Journal of Geophysical Research: Atmospheres 122, no. 17 (2017): 9211–32. http://dx.doi.org/10.1002/2017jd027615.

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Datta, Priyankar, and Manas Chandra Ray. "Effect of carbon nanotube waviness on smart damping of geometrically nonlinear vibrations of fuzzy-fiber reinforced composite plates." Journal of Intelligent Material Systems and Structures 30, no. 7 (2019): 977–97. http://dx.doi.org/10.1177/1045389x19828481.

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In this article, we present a finite element model for the three-dimensional analysis of smart constrained layer damping of geometrically nonlinear vibrations of laminated fuzzy-fiber reinforced composite plates. The three-dimensional fractional derivative constitutive relation is implemented for the viscoelastic layer. The constraining layer of the smart constrained layer damping treatment is composed of the vertically/obliquely reinforced 1–3 piezoelectric composites. The von Kármán–type nonlinear strain–displacement relations are used to incorporate the geometric nonlinearity in the model. The main aim of this article is to numerically investigate the effect of carbon nanotube waviness on the nonlinear smart damping. Several thin laminated substrate fuzzy-fiber reinforced composite plates with straight carbon nanotubes and wavy carbon nanotubes with different waviness in different planes are considered with various boundary conditions and stacking sequences to numerically compute their effect on smart damping. The performance of the obliquely reinforced 1–3 piezoelectric composites is discussed and the efficacy of the present smart finite element model in terms of active control authority is also presented.

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Kovalnogov, Vladislav N., Ruslan V. Fedorov, Andrei V. Chukalin, Mariya I. Kornilova, Tamara V. Karpukhina, and Anton V. Petrov. "Application of Intelligent and Digital Technologies to the Tasks of Wind Energy." Energies 16, no. 1 (2023): 481. http://dx.doi.org/10.3390/en16010481.

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The article considers the relevance and issues of wind turbine modeling, the principles of wind energy conversion (WEC) system operation, working areas and regulation. The influence of soft computing technologies on the different aspects of wind power systems, particularly in the fields of operation and maintenance, is considered. This article discusses the recent research, development and trends in soft computing techniques for wind-energy-conversion systems. For reliable analysis, the interaction of the wind-generator operation with the atmospheric boundary layer is considered. The authors give a detailed description of the approaches for the study and numerical modeling of the atmospheric boundary layer (ABL) in the vicinity of a wind farm. The study of the atmospheric boundary layer in the vicinity of the Ulyanovsk wind farm on the basis of cluster analysis of meteorological data is performed. Ten localizations of ABL homogeneous properties are identified. The subject of the study is the application of the results of cluster analysis to set linguistic variables in fuzzy inference algorithms as well as to adjust the initial conditions in the digital model of a wind generator. The results of cluster analysis made it possible to reasonably construct membership functions for the wind speed value in the fuzzy control algorithm to limit the output power of wind turbines. A simulation of the operation of a three-bladed horizontal type wind turbine for the conditions of one of the resulting clusters is performed, and the main regularities of the flow around the wind turbine are revealed. The results obtained are a valuable source for assessing the mutual influence of wind farms and the environment as well as wind farm site development.

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Lu, Yong-Kun. "Adaptive Fuzzy Integral Sliding-Mode Regulator for Induction Motor Using Nonlinear Sliding Surface." International Journal of Power Electronics and Drive Systems (IJPEDS) 5, no. 4 (2015): 512. http://dx.doi.org/10.11591/ijpeds.v5.i4.pp512-519.

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An adaptive fuzzy integral sliding-mode controller using nonlinear sliding surface is designed for the speed regulator of a field-oriented induction motor drive in this paper. Combining the conventional integral sliding surface with fractional-order integral, a nonlinear sliding surface is proposed for the integral sliding-mode speed control, which can overcome the windup problem and the convergence speed problem. An adaptive fuzzy control term is utilized to approximate the uncertainty. The stability of the controller is analyzed by Lyapunov stability theory. The effectiveness of the proposed speed regulator is demonstrated by the simulation results in comparison with the conventional integral sliding-mode controller based on boundary layer.

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Grabowska, Karolina, Jarosław Krzywański, Karol Sztekler, Wojciech Kalawa, and Wojciech Nowak. "Fuzzy logic approach in the analysis of heat transfer in a porous sorbent bed of the adsorption chiller." Technical Sciences 4, no. 21 (2018): 281–90. http://dx.doi.org/10.31648/ts.4173.

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Thermal conductivity in the boundary layer of heat exchange surface is the crucial parameter of adsorption process efficiency which occurs in the adsorption bed. In order to improve heat transfer conditions in the adsorption chiller, novel constructions of adsorption beds are currently investigated. The porous structure of the sorbent layer causes low thermal conductivity in the adsorption bed. One of the methods to improve heat transfer conditions is a modification of porous media bed structure with glue which is characterized with higher thermal conductivity. The optimum parameters of sorbents and glues to build the novel coated construction, in terms of improving the chiller Coefficient of Performance (COP) were defined in (Grabowska et al. 2018a). The paper implements fuzzy logic approach for predicting thermal conductivity of modified porous media layers. The developed model allows determination of the sorbent layer thermal conductivity based on various input parameters: arithmetic average of particle distribution d, density ρ and thermal diffusivity k. The data from empirical research was used to build up the model by fuzzy logic methods.

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Yarahmadi, Majid, and Somayeh Chegini. "Indirect fuzzy sliding mode control with varying boundary layer via time-variant sliding function." Journal of Intelligent & Fuzzy Systems 33, no. 3 (2017): 1541–51. http://dx.doi.org/10.3233/jifs-17019.

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Choi, Byung-Jae, Seong-Woo Kwak, and Byung Kook Kim. "Fuzzy Logic-Based Tuning of the Boundary Layer Thickness of the Variable Structure Controller." Intelligent Automation & Soft Computing 4, no. 3 (1998): 241–51. http://dx.doi.org/10.1080/10798587.1998.10750734.

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Wei, Jingxin, and Xiaoyu Zhang. "Fuzzy Logic Adaptive Online Optimization of Sliding Mode Control with Boundary Layer Self-tuning." International Journal of Control and Automation 10, no. 4 (2017): 357–66. http://dx.doi.org/10.14257/ijca.2017.10.4.32.

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Guo, Jinghua, Yugong Luo, Keqiang Li, and Rongben Wang. "A novel fuzzy-sliding automatic speed control of intelligent vehicles with adaptive boundary layer." International Journal of Vehicle Design 73, no. 4 (2017): 300. http://dx.doi.org/10.1504/ijvd.2017.083420.

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Wang, Rongben, Jinghua Guo, Yugong Luo, and Keqiang Li. "A novel fuzzy-sliding automatic speed control of intelligent vehicles with adaptive boundary layer." International Journal of Vehicle Design 73, no. 4 (2017): 300. http://dx.doi.org/10.1504/ijvd.2017.10004142.

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Tanamachi, Robin L., Stephen J. Frasier, Joseph Waldinger, Allison LaFleur, David D. Turner, and Francesc Rocadenbosch. "Progress toward Characterization of the Atmospheric Boundary Layer over Northern Alabama Using Observations by a Vertically Pointing, S-Band Profiling Radar during VORTEX-Southeast." Journal of Atmospheric and Oceanic Technology 36, no. 11 (2019): 2221–46. http://dx.doi.org/10.1175/jtech-d-18-0224.1.

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AbstractDuring spring 2016 and spring 2017, a vertically pointing, S-band Frequency Modulated Continuous Wave radar (UMass FMCW) was deployed in northern Alabama under the auspices of the Verification of the Origins of Rotation in Tornadoes Experiment (VORTEX)-Southeast. In total, ~14 weeks of data were collected, in conditions ranging from quiescent clear skies to severe thunderstorms. The principal objective of these deployments was to characterize the boundary layer evolution near the VORTEX-Southeast domain. In this paper, we describe intermediate results in service of this objective. Specifically, we describe updates to the UMass FMCW system, document its deployments for VORTEX-Southeast, and apply four automated algorithms: 1) a dealiasing algorithm to the Doppler velocities, 2) a fuzzy logic scatterer classification scheme to separate precipitation from nonprecipitation observations, 3) a brightband/melting-layer identification algorithm for stratiform precipitation, and 4) an extended Kalman filter–based convective boundary layer depth (mixing height) measurement algorithm for nonprecipitation observations. Results from the latter two applications are qualitatively verified against retrieved soundings from a collocated thermodynamic profiling system.

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Wang, Yingbo, Changle Sun, Haipeng Sun, Xiaolin Zhang, and Tingrui Liu. "Flutter Suppression of Wind Turbine Blade based on Adaptive Fuzzy Sliding Mode Control." Journal of Physics: Conference Series 2173, no. 1 (2022): 012029. http://dx.doi.org/10.1088/1742-6596/2173/1/012029.

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Abstract Aiming at the divergent unstable vibration of wind turbine blades, an adaptive fuzzy sliding mode control algorithm based on sliding mode control is proposed to solve the classic flutter fracture failure problem of blades. The structural model is a typical blade section model based on spring-mass-damper, and the aeroelastic equation is obtained by combining the steady aerodynamic model suitable for pure pitch motion. The adaptive fuzzy sliding mode controller gives the pitch signal, and the second-order pitch actuator performs the pitch action to suppress flutter. The saturation function with variable boundary layer thickness is used instead of symbolic function, and the approach rate parameter is adjusted appropriately by fuzzy rules, so as to realize variable-parameter adaptive fuzzy sliding mode control. Simulation results show that, compared with the traditional sliding mode controller, the proposed control algorithm can not only suppress the classical flutter, but also effectively reduce the amplitude and frequency of chattering, and has good robustness.

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Begnini, Mauricio, Douglas Wildgrube Bertol, and Nardênio Almeida Martins. "Design of an adaptive fuzzy variable structure compensator for the nonholonomic mobile robot in trajectory tracking task." Control and Cybernetics 47, no. 3 (2018): 239——275. https://doi.org/10.5281/zenodo.4282917.

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A robust adaptive kinematic control strategy, based on the methodology of variable structure control is considered in this paper. Because the dynamics of mobile robots is subject to uncertainties and disturbances, a fuzzy compensator is adopted to estimate them. In order to minimize the tracking errors and to attenuate the chattering phenomenon, an adaptation law for the fuzzy compensator is obtained by Lyapunov stability theory so as to asymptotically stabilize the control system as well as guarantee the convergence of the tracking errors. In terms of comparison with the boundary layer variable structure controller, simulations and experiments verify the feasibility and effectiveness of the proposed kinematic control strategy for the nonholonomic mobile robots under the incidence of uncertainties and disturbances.

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Bianco, Laura, and James M. Wilczak. "Convective Boundary Layer Depth: Improved Measurement by Doppler Radar Wind Profiler Using Fuzzy Logic Methods." Journal of Atmospheric and Oceanic Technology 19, no. 11 (2002): 1745–58. http://dx.doi.org/10.1175/1520-0426(2002)019<1745:cbldim>2.0.co;2.

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Kapovskiy, Boris R., Viktoriya A. Pchelkina, and Andrey S. Dydykin. "Application of Fuzzy and Clear Mathematical Models in Hybrid Control of the Process of Single-Stage Mincing of Frozen Meat." Engineering Technologies and Systems 4, no. 33 (2023): 558–84. http://dx.doi.org/10.15507/2658-4123.033.202304.558-584.

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Introduction. During one-stage mincing of frozen meat by milling, a change in the temperature of the boundary layer occurs resulting in plastic deformations of the raw meat and an increase in the size of the meat chips. The problem of regulating the operating parameters for the raw meat mincing process depending on its temperature can be solved through computer calculations of the temperature forecast of the meat boundary layer for several time intervals using fuzzy logic. The aim of the study was to develop an algorithm for hybrid control of single-stage mincing of frozen meat using fuzzy and clear mathematical control models. Aim of the Article. The article is aimed at developing a hybrid control algorithm for singlestage grinding of frozen meat using fuzzy and clear mathematical control models. Materials and Methods. The object of the study was the process of mincing frozen meat block (beef) with the use of a laboratory installation for a single-stage mincing with a capacity of 400 kg/hour. The E. Mamdani algorithm was used to develop a fuzzy mathematical control model. Mathematical modeling was carried out in the MATLAB, the Fuzzy Logic Toolbox package. Results. There was developed a model for fuzzy control of the operation of an intelligent control system (ICS) when forming a task for setting the operating parameters of the meat mincing process with the use of adaptive forecasting of meat temperature. For this model, the membership functions of the input and output variables and a rule base (knowledge base) were created. There was proposed a functional scheme of temperature control, which reflects the structure of a fuzzy control model for single-stage mincing. The advantages of this control include the fact that the system is given the function of continuous automated control of the temperature regime of mincing raw meat under the control of an industrial computer. Discussion and Conclusion. The results of temperature control can be used for further technological processing of meat. Using information about the temperature and chemical composition of raw meat, the ICS can realize the optimal mixing of minced meat ingredients. Artificial intelligence calculates all these characteristics of meat without the participation of a human operator. It makes it possible to fully automate the technological processing of meat in order to produce finished products of guaranteed high quality.

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Yao, Guozhong, Xianxiang Wang, Zhengjiang Wang, and Yuhan Xiao. "Senseless Control of Permanent Magnet Synchronous Motors Based on New Fuzzy Adaptive Sliding Mode Observer." Electronics 12, no. 15 (2023): 3266. http://dx.doi.org/10.3390/electronics12153266.

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Based on the problems of sliding mode observer (SMO), such as strong parameter dependency, large overshoot, and severe inherent sliding mode chattering, this paper studies fuzzy control in depth using a sigmoid (s) function with smooth and continuous characteristics instead of a discontinuous symbolic function to design a new type of fuzzy sliding mode observer. Firstly, the boundary layer thickness was introduced to enable the system to achieve adaptive sliding mode gain adjustment based on the system state. Then, based on PLL technology, PI adjustment was used to obtain rotor position information. Finally, in order to verify the effectiveness of the new method, a model was built for experimental verification, and the simulation waveforms of the traditional sliding mode observer and the new fuzzy sliding mode observer were compared. The results show that the new fuzzy sliding mode observer can more accurately estimate rotor position and speed information. Under the same operating conditions, the rotational speed estimation error is only 3 r/min, the rotor position error is reduced by 0.1 rad, the overshoot is smaller, and the chattering is significantly reduced.

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Makhloufi, Khadidja, Ismail Khalil Bousserhane, and Si Ahmed Zegnoun. "Adaptive fuzzy sliding mode controller design for PMLSM position control." International Journal of Power Electronics and Drive Systems (IJPEDS) 12, no. 2 (2021): 674. http://dx.doi.org/10.11591/ijpeds.v12.i2.pp674-684.

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We focus a modern methodology in this paper for adding the fuzzy logic control as well as sliding model control. This combination can enhance the MLS position control robustness and enhanced performance of it.In the start, for an application in an area to control the loops placement and position for the synchronous motor what has permanent magnetic linearity we tend to control the fuzzy sliding mode control. To resolve the chattering issues a designed controller is investigated and, in this way, steady state motion in sliding with higher accuracy is obtained. In this case, method of online tuning with the help of fuzzy logic is used in order to adjust the thickness of boundary layer and switching gains.For the suggested scheme technique, the outcomes of simulation suggest that with the classical SMC the accurate state and good dynamic performance is compared due to force chattering resistance, response by quick dynamic force and external disturbance elements and robustness against them.

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Nakamura Goto, Willy John, Douglas Wildgrube Bertol, and Nardênio Almeida Martins. "Adaptive Imune Fuzzy Quasi-Sliding Mode Formation Tracking Control for Wheeled Mobile Robots with Obstacle Avoidance Under Incidence of Uncertainties and Disturbances: An Artificial Immune Systems Inspired Approach." Learning and Nonlinear Models 22, no. 1 (2024): 61–95. http://dx.doi.org/10.21528/lnlm-vol22-no1-art5.

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This paper presents an adaptive immune fuzzy quasi-sliding mode kinematic control integrated with a PD dynamic control for the trajectory tracking and the leader-follower formation control by nonholonomic differential-drive wheeled mobile robots under incidence of uncertainties and disturbances. An immune regulation mechanism bio-inspired approach with reaction effect established by novel fuzzy rules set to adjust the control effort adaptively is designed, also using a fuzzy boundary layer and introducing an adaptation law for the immune portion gain online adjustment in such a way that they can also avert parameter drift, dealing with the drawbacks of a classic first-order sliding mode control, suppressing chattering and still maintaining the robustness with no a priori knowledge of the bounds of the disturbances. An obstacle avoidance strategy with a reactive method and variable avoidance radius is also proposed. The stability analysis is performed based on the Lyapunov theory. Simulation results demonstrate the proposed control effectiveness.

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Khadidja, Makhloufi, Khalil Bousserhane Ismail, and Ahmed Zegnoun Si. "Adaptive fuzzy sliding mode controller design for PMLSM position control." International Journal of Power Electronics and Drive System (IJPEDS) 12, no. 2 (2021): 674–84. https://doi.org/10.11591/ijpeds.v12.i2.pp674-684.

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We focus a modern methodology in this paper for adding the fuzzy logic control as well as sliding model control. This combination can enhance the PMLSM position control robustness and enhanced performance of it. In the start, for an application in an area to control the loops placement and position for the synchronous motor what has permanent magnetic linearity we tend to control the fuzzy sliding mode control. To resolve the chattering issues a designed controller is investigated and, in this way, steady state motion in sliding with higher accuracy is obtained. In this case, method of online tuning with the help of fuzzy logic is used in order to adjust the thickness of boundary layer and switching gains. For the suggested scheme technique, the outcomes of simulation suggest that with the classical SMC the accurate state and good dynamic performance is compared due to force chattering resistance, response by quick dynamic force and external disturbance elements and robustness against them.

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35

Bazzi, B. A., and N. G. Chalhoub. "Fuzzy Sliding Mode Controller for a Flexible Single-Link Robotic Manipulator." Journal of Vibration and Control 11, no. 2 (2005): 295–314. http://dx.doi.org/10.1177/1077546305049480.

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Two robust non-linear controllers have been developed in this study to control the rigid and flexible motions of a single-link robotic manipulator. The controllers consist of a conventional sliding mode controller (CSMC) and a fuzzy sliding mode controller (FSMC). The effects of fuzzy-tuning some of the CSMC control parameters on the overall performance of the arm have been investigated in this study. Furthermore, the proposed FSMC, whose parameters are determined by fuzzy inference systems, has been designed herein based on two Lyapunov functions. The rationale is to considerably reduce the momentum of the system before entering the boundary layer neighboring the sliding surface. This will significantly attenuate the structural deformations of the arm. The digital simulations have demonstrated that the structural deformations, incurred by the beam at the onset of its movement, can be significantly reduced by fuzzy-tuning some of the control parameters. Furthermore, the results have illustrated the superiority of the FSMC over the CSMC in producing a less oscillatory and more accurate response of the angular displacement at the base joint, in damping out the unwanted vibrations of the beam, and in requiring significantly smaller control torques.

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Mao, Jin, Lei Yang, Yuanbo Hu, Kai Liu, and Jinfu Du. "Research on Vehicle Adaptive Cruise Control Method Based on Fuzzy Model Predictive Control." Machines 9, no. 8 (2021): 160. http://dx.doi.org/10.3390/machines9080160.

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Under complex working conditions, vehicle adaptive cruise control (ACC) systems with fixed weight coefficients cannot guarantee good car following performance under all conditions. In order to improve the tracking and comfort of vehicles in different modes, a fuzzy model predictive control (Fuzzy-MPC) algorithm is proposed. Based on the comprehensive consideration of safety, comfort, fuel economy and vehicle limitations, the objective function and constraints are designed. A relaxation factor vector is introduced to soften the hard constraint boundary in order to solve this problem, for which there was previously no feasible solution. In order to maintain driving stability under complex conditions, a multi-objective optimization method, which can update the weight coefficient online, is proposed. In the numerical simulation, the values of velocity, relative distance, acceleration and acceleration change rate under different conditions are compared, and the results show that the proposed algorithm has better tracking and stability than the traditional algorithm. The effectiveness and reliability of the Fuzzy-MPC algorithm are verified by co-simulation with the designed PID lower layer control algorithm with front feedforward and feedback.

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Barhoi, Amir, G. C. Hazarika, Hrishikesh Baruah, and Pranjal Borah. "Numerical Solution of Radiative Boundary Layer Flow in Porous Medium Due to Exponentially Shrinking Permeable Sheet Under Fuzzy Environment." East European Journal of Physics, no. 2 (June 2, 2023): 107–16. http://dx.doi.org/10.26565/2312-4334-2023-2-09.

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In this paper we are considering a fluid flows problem that contains two equation of motions and more than two parameters in the governing equation of motion. Which is namely Radiative Boundary Layer Flow in Porous Medium due to Exponentially Shrinking Permeable Sheet. The parameter are K=ck0/Lθ, Pr=μcp/κ∞, N=4σ1(T∞)3/(3κ1κ∞), and ε denote the permeability parameter, Prandtl number, and radiation parameter and is the thermal conductivity variation parameter, respectively. The governing differential equation can be obtained by using the similarity variable technique, and then the governing equation of motion can be Fuzzified by the help of Zadeh extension theorem. The technique is used for the validation of the uncertainty of the equation of the motion. The effect of the K, Pr, N, and ε are discussed with the fuzzified governing equation of motion under fuzzy environment. It is observed none of the parameters are directly involved in the occurrence of the uncertainty of the solutions. The uncertainty occurs in the problem is due to the assumption and the numerical computation. Finally, the solution is being carried out under fuzzy environment. It is found that the increasing values of permeability parameter, the values of both the numbers Skin friction coefficient as well as Nusselt number are increases.

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Siddique, Imran, Yasir Khan, Muhammad Nadeem, Jan Awrejcewicz, and Muhammad Bilal. "Significance of heat transfer for second-grade fuzzy hybrid nanofluid flow over a stretching/shrinking Riga wedge." AIMS Mathematics 8, no. 1 (2023): 295–316. http://dx.doi.org/10.3934/math.2023014.

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<abstract> <p>This investigation presents the fuzzy nanoparticle volume fraction on heat transfer of second-grade hybrid $ {\text{A}}{{\text{l}}_{\text{2}}}{{\text{O}}_{\text{3}}}{\text{ + Cu/EO}} $ nanofluid over a stretching/shrinking Riga wedge under the contribution of heat source, stagnation point, and nonlinear thermal radiation. Also, this inquiry includes flow simulations using modified Hartmann number, boundary wall slip and heat convective boundary condition. Engine oil is used as the host fluid and two distinct nanomaterials ($ {\text{Cu}} $ and $ {\text{A}}{{\text{l}}_{\text{2}}}{{\text{O}}_{\text{3}}} $) are used as nanoparticles. The associated nonlinear governing PDEs are intended to be reduced into ODEs using suitable transformations. After that 'bvp4c, ' a MATLAB technique is used to compute the solution of said problem. For validation, the current findings are consistent with those previously published. The temperature of the hybrid nanofluid rises significantly more quickly than the temperature of the second-grade fluid, for larger values of the wedge angle parameter, the volume percentage of nanomaterials. For improvements to the wedge angle and Hartmann parameter, the skin friction factor improves. Also, for the comparison of nanofluids and hybrid nanofluids through membership function (MF), the nanoparticle volume fraction is taken as a triangular fuzzy number (TFN) in this work. Membership function and $ \sigma {\text{ - cut}} $ are controlled TFN which ranges from 0 to 1. According to the fuzzy analysis, the hybrid nanofluid gives a more heat transfer rate as compared to nanofluids. Heat transfer and boundary layer flow at wedges have recently received a lot of attention due to several metallurgical and engineering physical applications such as continuous casting, metal extrusion, wire drawing, plastic, hot rolling, crystal growing, fibreglass and paper manufacturing.</p> </abstract>

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Cui, Y. X., B. Shen, F. H. Sun, and Z. M. Zhang. "Selective Growth of B-Doped Diamond on Si-Doped Diamond Film." Applied Mechanics and Materials 217-219 (November 2012): 1013–17. http://dx.doi.org/10.4028/www.scientific.net/amm.217-219.1013.

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Si doped CVD diamond films are prepared on Si substrate by means of hot filament chemical vapor deposition (HFCVD) through adding tetraethoxysilane (TEOS) into acetone as source of reactant gas during the growth process. The samples of diamond films are investigated by scanning electron micrograph (SEM), Raman spectrum, X-ray diffractometry (XRD) and surface profiler. The experimental results show that compared with pure diamond film, Si doped CVD diamond film exhibits grain refinement and smoother surface. Then selective area deposition (SAD) of B-doped diamond films are achieved on both Si doped CVD diamond film and pure CVD diamond film with silicon dioxide layer as sacrificial layer. SEM investigation demonstrates that the boundary of patterning on pure diamond film is rather fuzzy while on pure diamond film it is trim and distinct, which is mainly attributed to the relatively low surface roughness.

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Saghafinia, Ali, Hew Ping, and Mohammad Uddin. "Sensored Field Oriented Control of a Robust Induction Motor Drive Using a Novel Boundary Layer Fuzzy Controller." Sensors 13, no. 12 (2013): 17025–56. http://dx.doi.org/10.3390/s131217025.

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Saghafinia, Ali, Hew Wooi Ping, and M. Nasir Uddin. "Fuzzy sliding mode control based on boundary layer theory for chattering-free and robust induction motor drive." International Journal of Advanced Manufacturing Technology 71, no. 1-4 (2013): 57–68. http://dx.doi.org/10.1007/s00170-013-5398-7.

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Nan, Yu, Lei Wang, Meng Qi, and Zhi Li. "Design of Variable Boundary Layer Sliding Mode Observer for Permanent Magnet Synchronous Motor Based on Fuzzy Control." Progress In Electromagnetics Research C 154 (2025): 119–29. https://doi.org/10.2528/pierc25013101.

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Zhang, Chunli, Xu Tian, and Lei Yan. "FLS-Based Nonuniform Trajectory Tracking AILC for Uncertain Nonlinear Systems with Nonsymmetric Dead-Zone Input and Initial State Error." Mathematical Problems in Engineering 2021 (August 18, 2021): 1–9. http://dx.doi.org/10.1155/2021/3351074.

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This paper proposes an AILC method for uncertain nonlinear system to solve different target tracking problems. The method uses fuzzy logic systems (FLS) to approximate every uncertain term in systems. All closed-loop signals are bounded on 0 , T according to the Lyapunov theory. A time-varying boundary layer and a typical convergent series are introduced to handle initial state error, unknown bounds of errors, and nonuniform target tracking, respectively. The result is that the tracking error’s norm can converge to a small neighborhood along iteration increasing asymptotically. Finally, the simulation results of mass-spring mechanical system show the correctness of the theory and validity of the method.

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Shao, Fan, Kai Wang, and Yanluo Liu. "Salient object detection algorithm based on diversity features and global guidance information." Innovation & Technology Advances 1, no. 1 (2023): 12–20. http://dx.doi.org/10.61187/ita.v1i1.14.

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Aiming at the problems of traditional salient object detection methods such as fuzzy boundary and insufficient information integrity, a salient object detection network composed of feature diversity enhancement module, global information guidance module and feature fusion module is proposed. Firstly, asymmetric convolution, cavity convolution and common convolution are spliced to form a feature diversity enhancement module to extract different types of spatial features corresponding to each feature layer. Secondly, the global information guidance module transmits the information captured by the coordinate attention mechanism to each feature layer through the global guidance stream, so as to learn the semantic relationship between different feature layers and alleviate the dilution effect; Finally, the feature fusion module receives the high-level features output from the previous layer, the low-level features of the corresponding layer and the global context information generated by the global information guidance module, and the cascade feature diversity enhancement module gradually integrates the multi-level features to refine the saliency feature map. Comparative experiments on five public data sets show that this method can achieve the highest values of 0.959 and 0.030 in F-measure and MAE. Compared with other seven advanced algorithms, it has better detection performance.

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Li, Yan, and Lianhui Li. "Enhancing the Optimization of the Selection of a Product Service System Scheme: A Digital Twin-Driven Framework." Strojniški vestnik – Journal of Mechanical Engineering 66, no. 9 (2020): 534–43. http://dx.doi.org/10.5545/sv-jme.2020.6621.

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A product service system (PSS) has been developed for manufacturing enterprises to provide users with personalized products and services. The optimization of PSS scheme selection is a key stage in the PSS design phase. Given the dynamic characteristics of the multi-dimensional influencing factors and their coupling relationships, we propose a digital twin-driven framework to enhance the optimization of PSS scheme selection. The framework is divided into a digital twin layer, an information layer, and an approach layer. The logical relationship between the three layers is given, and a quantitative PSS scheme selection optimization mechanism is designed. Fuzzy numbers and rough boundary intervals are integrated for the attribute value determination of the PSS scheme. A modified TOPSIS developed by replacing Euclidean distance with relational vector distance is adopted for the PSS scheme assessment. A case of an air purification PSS scheme selection optimization under the proposed digital twin driven framework is studied. It is shown that the designed PSS scheme selection optimization mechanism is effective and can be enhanced with the presented framework.

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Krajči, Vesna, and Igor Krajči. "Comparison of robot trajectory tracking efficiency using various nonlinear control methods." Zbornik Veleučilišta u Rijeci 6, no. 1 (2018): 299–13. http://dx.doi.org/10.31784/zvr.6.1.20.

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The Denavit-Hartenberg algorithm and the Lagrange-Euler method are used to derive realistic kinematics and dynamic models of a three-axis electric driven articulated planar robot with viscous, dynamic and static frictions. These robot models are further used for testing the following presented nonlinear robot control methods: fuzzy control, variable-structure control and model-reference variable-structure control. In the fuzzy-logic control method seven fuzzy sets are defined for two input variables. Triangular input membership functions and the 7x7 fuzzy rule table are chosen. The fuzzy controller output value is calculated according to the centre of gravity principle. The same fuzzy control algorithm is used in all robot servo control loops with a proper scaling of the linguistic variables. To eliminate the chattering of the variable-structure control signal and to reduce energy consumption, sign function in the original variable-structure control law is replaced with the following functions: a continuous, saturation and exponential function, all of them with a very thin boundary layer. The same modifications are also made in the original model-reference variable-structure control method. In all presented control methods controller parameters are chosen according to the principle of maximal allowed tracking error and a minimum of energy consumption. These control methods are tested by computer simulations in C programming language in the case of moving the tool of the chosen robot arm. The simulation results proved similar efficiencies of all mentioned modified nonlinear robot control methods, although modified variable structure control algorithms are the most suitable because of their simplicity and lower number of controller parameters.

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Norouzi, Armin, Reza Kazemi, and Shahram Azadi. "Vehicle lateral control in the presence of uncertainty for lane change maneuver using adaptive sliding mode control with fuzzy boundary layer." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 232, no. 1 (2017): 12–28. http://dx.doi.org/10.1177/0959651817733222.

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Recent researches on advanced driver-assistance systems indicate great advances in terms of safety and comfort in automated driving. Advanced driver-assistance systems use control systems to perform most of the maneuvers as performed by the driver in the past. One of the useful advanced driver-assistance systems is automatic lane change system in order to avoid accidents. This study designs the controller of an automatic lane change system for an autonomous vehicle. The control law in this study is adaptive sliding mode control. To avoid chattering in adaptive sliding mode control, fuzzy boundary layer is used. Also, adaptive law is used for sliding-based switching gain. This adaptive controlling law is used to avoid the calculation of upper bound of system uncertainties. In this study, based on the boundary conditions, the vehicle lane change path planning and different maneuver periods are evaluated. To simulate the designed controller, CarSim–Simulink joint simulation model is used. This linkage leads to a full non-linear vehicle model. The results of simulation show excellent tracking for dry road conditions and acceptable tracking in icy and wet roads in some maneuvers of above 4-s long.

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Erbatur, Kemalettin, and Berk Çallı. "Fuzzy boundary layer tuning for sliding mode systems as applied to the control of a direct drive robot." Soft Computing 13, no. 11 (2008): 1099–111. http://dx.doi.org/10.1007/s00500-008-0383-z.

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Li, Gang, Zhiyong Ruan, Ruiheng Gu, and Guoliang Hu. "Fuzzy Sliding Mode Control of Vehicle Magnetorheological Semi-Active Air Suspension." Applied Sciences 11, no. 22 (2021): 10925. http://dx.doi.org/10.3390/app112210925.

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In order to reduce vehicle vibration during driving conditions, a fuzzy sliding mode control strategy (FSMC) for semi-active air suspension based on the magnetorheological (MR) damper is proposed. The MR damper used in the semi-active air suspension system was tested and analyzed. Based on the experimental data, the genetic algorithm was used to identify the parameters of the improved hyperbolic tangent model, which was derived for the MR damper. At the same time, an adaptive neuro fuzzy inference system (ANFIS) was used to build the reverse model of the MR damper. The model of a quarter vehicle semi-active air suspension system equipped with a MR damper was established. Aiming at the uncertainty of the air suspension system, fuzzy control was used to adjust the boundary layer of the sliding mode control, which can effectively suppress the influence of chattering on the control accuracy and ensure system stability. Taking random road excitation and impact road excitation as the input signal, the simulation analysis of passive air suspension, semi-active air suspension based on SMC and FSMC was carried out, respectively. The results show that the semi-active air suspension based on FSMC has better vibration attenuating performance and ride comfort.

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Oveisi, Atta, and Tamara Nestorovic. "Mixed Kalman-Fuzzy Sliding Mode State Observer in Disturbance Rejection Control of a Vibrating Smart Structure." International Journal of Acoustics and Vibration 24, no. 4 (2019): 677–86. http://dx.doi.org/10.20855/ijav.2019.24.41365.

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In the controllers that are synthesized on a nominal model of a nonlinear plant, the parametric matched uncertainties and nonlinear/unmodelled dynamics of the high order nature can significantly affect the performance of the closed-loop system. On this note, owing to the robust characteristic of the sliding mode observer against modelling perturbations, measurement noise, and unknown disturbances and due to the non-fragile behaviour of the Kalman filter against process noise, a mixed Kalman sliding mode state-observer is proposed and later enhanced by the addition of an intelligent fuzzy agent. In light of the proposed technique, the chattering phenomena and the conservative boundary neighboring layer of the high gain sliding mode observer are addressed. Then, a robust active disturbance rejection controller is developed by using the static feedback of the estimated states using a~direct Lyapunov quadratic stability theorem. The reduced order plant for control design purposes is subjected to some simulated square-integrable disturbances and is assumed to have mismatched uncertainties in the system matrices. Finally, the robust performance of the closed-loop scheme with respect to the mentioned perturbation signals and modelling imperfections is tested by implementing the control system on a mechanical vibrating smart cantilever beam.

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Journal articles on the topic 'Fuzzy boundary layer'

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