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Journal articles on the topic 'Augmented proportional-integral-derivative controller'
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1
Varga, Balázs, Balázs Kulcsár, Leo Laine, Manjurul Islam, and Balázs Németh. "Robust tracking controller design for active dolly steering." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 232, no. 5 (2017): 695–706. http://dx.doi.org/10.1177/0954407017704779.
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In this paper, different actuation level steering control methods for an A-double vehicle combination (tractor–semitrailer–dolly–semitrailer) are proposed. The aim of the paper is to show the viability of advanced actuation control strategies for a practical vehicular application. Three different types of robust controller are proposed: a robust proportional–integral–derivative controller, an output feedback linear ℋ∞ controller and an induced ℒ2-norm minimizing linear parameter-varying controller. All controllers are augmented with anti-windup compensators to respect the steering-angle limit and the steering-rate limit. Each model-based controller robustly rejects external disturbances and tracks a reference steering angle generated by the motion control system. Frequency-domain analysis and time-domain analysis prove that the ℋ∞ controller and the linear parameter-varying controller outperform the proportional–integral–derivative controller in terms of reference tracking and disturbance rejection. Comparative simulation scenarios are provided on the basis of the high-fidelity vehicle simulator developed by Volvo Group Trucks Technology.
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Rahmadini, Vatia Fahrunisa, Alfian Ma'arif, and Nur Syuhadah Abu. "Design of Water Heater Temperature Control System using PID Control." Control Systems and Optimization Letters 1, no. 2 (2023): 111–17. http://dx.doi.org/10.59247/csol.v1i2.41.
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This research delves into advanced control methodologies by investigating the intricate applications of Proportional-Integral-Derivative (PID) control for achieving precise and dependable temperature regulation within electric water heaters. The study delves into various control strategies, namely Proportional, Proportional-Integral, and Proportional-Integral-Derivative methodologies, to realize the pinnacle of stable and exacting temperature control. The Proportional Controller, operating with a Kp value of 10, stands out with its relentless performance, characterized by minimal overshoot and an inconsequential steady-state error. Implementing the Proportional-Integral Controller, synergizing Kp at 10 and Ki at 5, elevates system stability while deftly curbing any hint of overshoot. The dynamic interplay between the Kp, Ki, and Kd parameters in the Proportional-Integral-Derivative (PID) Controller unveils an intricate dance of precision and control. Notably, configurations involving Kp 10, Ki 5, and Kd 2 emerge as beacons of rapid stabilization, heightened precision, and masterful overshoot management, exemplified by a rise time of 119.3543 seconds, settling time of 162.6116 seconds, overshoot of 1.0299%, peak time of 216 seconds, and a commendably low steady-state error of 0.31. This extensive exploration bears testament to its instrumental role in optimizing PID control strategies, ushering in augmented efficacy and pinpoint accuracy in water temperature regulation across an expansive spectrum of applications. As a result, these findings pave the way for the evolution of control methodologies that transcend theoretical confines and manifest within practical scenarios with profound impact.
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Krznar, Matija, Danijel Pavković, Mihael Cipek, and Juraj Benić. "Modeling, Controller Design and Simulation Groundwork on Multirotor Unmanned Aerial Vehicle Hybrid Power Unit." Energies 14, no. 21 (2021): 7125. http://dx.doi.org/10.3390/en14217125.
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This paper presents the results of modeling, control system design and simulation verification of a hybrid-electric drive topology suitable for power flow control within unmanned aerial vehicles (UAVs). The hybrid power system is based on the internal combustion engine (ICE) driving a brushless DC (BLDC) generator supplying the common DC bus used for power distribution within the aircraft. The overall control system features proportional-integral-derivative (PID) feedback control of the ICE rotational speed using a Luenberger estimator for engine-generator set rotational speed estimation. The BLDC generator active rectifier voltage and current are controlled by proportional-integral (PI) feedback controllers, augmented by estimator-based feed-forward load compensators. The overall control system design has been based on damping optimum criterion, which yields straightforward analytical expressions for controller and estimator parameters. The robustness to key process parameters variations is investigated by means of root-locus methodology, and the effectiveness of the proposed hybrid power unit control system is verified by means of comprehensive computer simulations.
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Li, XianHong, HaiBin Yu та MingZhe Yuan. "Design of Optimal PID Controller withɛ-Routh Stability for Different Processes". Mathematical Problems in Engineering 2013 (2013): 1–22. http://dx.doi.org/10.1155/2013/582879.
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This paper presents a design method of the optimal proportional-integral-derivative (PID) controller withɛ-Routh stability for different processes through Lyapunov approach. The optimal PID controller could be acquired by minimizing an augmented integral squared error (AISE) performance index which contains control error and at least first-order error derivative, or even may containnth-order error derivative. The optimal control problem could be transformed into a nonlinear constraint optimization (NLCO) problem via Lyapunov theorems. Therefore, optimal PID controller could be obtained by solving NLCO problem through interior method or other optimization methods. The proposed method can be applied for different processes, and optimal PID controllers under various control weight matrices andɛ-Routh stability are presented for different processes. Control weight matrix andɛ-Routh stability’s effects on system performances are studied, and different tuning methods’ system performances are also discussed.ɛ-Routh stability’s effects on disturbance rejection ability are investigated, and different tuning methods’ disturbances rejection ability is studied. To further illustrate the proposed method, experimental results of coupled water tank system (CWTS) under different set points are presented. Both simulation results and experiment results show the effectiveness and usefulness of the proposed method.
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Abbas, H. Issa, A. Mahmood Sarab, T. Humod Abdulrahim, and M. Ameen Nihad. "Robustness enhancement study of augmented positive identification controller by a sigmoid function." International Journal of Artificial Intelligence (IJ-AI) 12, no. 2 (2023): 686–95. https://doi.org/10.11591/ijai.v12.i2.pp686-695.
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The dissolved oxygen concentration in the wastewater treatment process (WWTP) must remain in a specific range while the factory operates. The augmented positive identification (PID) controller with a nonlinear element (sigmoid function) is proposed to assure stability and reduce uncertainties in the wastewater direct reuse/recycling model. The nonlinear controller gains (PID controller with sigmoid function) for uncertain wastewater treatment processes are tuned using the particle swarm optimization (PSO) technique. The proposed robust method for controlling wastewater treatment processes has good robustness during model mismatching, reduces treatment time compared to traditional positive identification (PID) controllers tuned by PSO, is easy to apply, and has good performance, according to simulation results.
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Al-Badri, Kareem, Hussien Dulaimi, Huthaifa Al-Khazraji, and Amjad J. Humaidi. "Adaptive Neural Network Control for Load-Varying Two-Link Robots Using Honey Badger Optimization." Journal of Robotics and Control (JRC) 6, no. 2 (2025): 1061–68. https://doi.org/10.18196/jrc.v6i2.26370.
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This paper illustrates a proportional-integral-derivative based neural network (PID-NN) controller to manipulate the angular position of the two-link robot considering the load variation on the system. The two-link robot system's dynamic equations were derived using the Lagrange method. To improve the tuning process of the design coefficients of the controller, the learning process was framed as an optimization task. Subsequently, to determine the optimal weight values, the honey badger algorithm (HBA) was introduced. To analyze how well the proposed controller performs, Simulations in MATLAB were carried out to compare the PID-NN controller against a PI-PD controller. The findings revealed superior performance of the PID-NN controller in standard conditions. Furthermore, the PID-NN demonstrated a substantial enhancement when a load variation was augmented.
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Su, Khac Huan, Kwankyun Byeon, Wonhee Kim, and Youngwoo Lee. "LPV H∞ Control with an Augmented Nonlinear Observer for Sawyer Motors." Mathematics 10, no. 1 (2021): 18. http://dx.doi.org/10.3390/math10010018.
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This study presents LPV H∞ control with an augmented nonlinear observer (ANOB) to improve both the position and yaw tracking errors for Sawyer motors. The proposed control method consists of the forces and torque modulation scheme, an ANOB, and a Lyapunov-based current controller with the LPV H∞ state feedback controller to guarantee the stability of tracking error dynamics. The ANOB is designed to estimate all the state variables including the position, velocity, current, and disturbance using only position feedback. We propose a vertex expansion technique to solve the influence of the convex interpolation parameters in the LPV system on the tracking error performance. To be robust against disturbance, a state feedback controller with the LPV gain scheduling is determined by applying the H∞ control in the linear-matrix-inequality (LMI) technique. The closed-loop stability is proved through the Lyapunov theory. The effectiveness of the proposed control method is evaluated through simulation results and compared with the conventional proportional-integral-derivative (PID) control method to verify both the improved tracking error performance and a suitable disturbance rejection.
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Pataro, Igor, Vergel Juan Diego Gil, Jose Luis Guzman, and Joao M. Lemos. "Performance study of disturbance rejection in linear quadratic controllers: A practical adaptive tuning method." Revista Iberoamericana de Automática e Informática Industrial 21, no. 2 (2025): 148–58. https://doi.org/10.4995/riai.2023.19703.
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This paper proposes an adaptive tuning method for the Linear-Quadratic FeedForward (LQ-FF) optimal controller. The procedure aims to reject disturbances while maintaining the reference tracking performance of the conventional LQ controller. The adaptive mechanism is formulated by analyzing each element of the control signal LQ-FF concerning state regulation, reference change, and disturbance compensation. The disturbance rejection mechanism is based on the classical strategy used in Proportional-Integral-Derivative controllers and the theoretical analysis studied in previous works for predictive controllers, which aim to obtain the inverse dynamics of the disturbances and process inputs in relation to the outputs. In addition, a comparison is presented between an augmented state space model and a model with a polynomial delay approximation for treating delays associated with disturbances and process inputs in the controller formulation. The proposed method effectively controls a validated nonlinear temperature system, maintaining performance equivalent to the conventional LQ controller for reference tracking while entirely rejecting disturbance effects. The proposed tuning achieves 10 % less output error, with an increase of only 18 % in the control effort compared to conventional tuning in simulations.
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Alfian, Eriko, Alfian Ma'arif, Phichitphon Chotikunnan, and Ahmed Jaber Abougarair. "Optimizing Light Intensity with PID Control." Control Systems and Optimization Letters 1, no. 3 (2023): 124–31. http://dx.doi.org/10.59247/csol.v1i3.38.
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Lighting is a fundamental cornerstone within interior design, possessing the capability to metamorphose spaces and evoke emotional responses profoundly. This principle applies to residential, industrial, and office domains, where lighting nuances are meticulously adjusted to enhance comfort and practicality. However, adequate luminance frequently intersects with energy wastage, often attributed to negligent light management practices. Mitigating this issue necessitates integrating light intensity controls adept at adapting to ambient luminosity and room-specific parameters. A prospective avenue encompasses incorporating a Proportional Integral Derivative (PID) control system synergized with light sensors. This research Implementing a closed-loop architecture, PID control utilizes feedback mechanisms to improve the precision of instrumentation systems. The PID methodology, consisting of Proportional, Integral, and Derivative control modalities, produces stable responses, accelerates system reactions, and diminishes deviations and overshooting by predetermined setpoints. The proposed Light Intensity Control System underpinned by PID methodology manifests as an exhibition of compelling outcomes drawn from empirical trials. The judicious selection of optimal parameters, specifically Kp = 0.2, Ki = 0.1, and Kd = 0.1, yielded noteworthy test outcomes: an ascent time of 0.0848, an overshoot of 6.5900, a culmination period of 0.4800, a settling period of 2.3032, and a steady-state error of 0.0300. Within this system, the PID controller assumes a pivotal role, orchestrating the regulation and meticulous calibration of light intensity to harmonize with designated criteria, thus fostering an environment of augmented energy efficiency and adaptability in illumination.Lighting is a fundamental cornerstone within interior design, possessing the capability to metamorphose spaces and evoke emotional responses profoundly. This principle applies to residential, industrial, and office domains, where lighting nuances are meticulously adjusted to enhance comfort and practicality. However, adequate luminance frequently intersects with energy wastage, often attributed to negligent light management practices. Mitigating this issue necessitates integrating light intensity controls adept at adapting to ambient luminosity and room-specific parameters. A prospective avenue encompasses incorporating a Proportional Integral Derivative (PID) control system synergized with light sensors. This research Implementing a closed-loop architecture, PID control utilizes feedback mechanisms to improve the precision of instrumentation systems. The PID methodology, consisting of Proportional, Integral, and Derivative control modalities, produces stable responses, accelerates system reactions, and diminishes deviations and overshooting by predetermined setpoints. The proposed Light Intensity Control System underpinned by PID methodology manifests as an exhibition of compelling outcomes drawn from empirical trials. The judicious selection of optimal parameters, specifically Kp = 0.2, Ki = 0.1, and Kd = 0.1, yielded noteworthy test outcomes: an ascent time of 0.0848, an overshoot of 6.5900, a culmination period of 0.4800, a settling period of 2.3032, and a steady-state error of 0.0300. Within this system, the PID controller assumes a pivotal role, orchestrating the regulation and meticulous calibration of light intensity to harmonize with designated criteria, thus fostering an environment of augmented energy efficiency and adaptability in illumination.
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Saleem, Omer, Khalid Rasheed Ahmad, and Jamshed Iqbal. "Fuzzy-Augmented Model Reference Adaptive PID Control Law Design for Robust Voltage Regulation in DC–DC Buck Converters." Mathematics 12, no. 12 (2024): 1893. http://dx.doi.org/10.3390/math12121893.
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This paper presents a novel fuzzy-augmented model reference adaptive voltage regulation strategy for the DC–DC buck converters to enhance their resilience against random input variations and load-step transients. The ubiquitous proportional-integral-derivative (PID) controller is employed as the baseline scheme, whose gains are tuned offline via a pre-calibrated linear-quadratic optimization scheme. However, owing to the inefficacy of the fixed-gain PID controller against parametric disturbances, it is retrofitted with a model reference adaptive controller that uses Lyapunov gain adaptation law for the online modification of PID gains. The adaptive controller is also augmented with an auxiliary fuzzy self-regulation system that acts as a superior regulator to dynamically update the adaptation rates of the Lyapunov gain adaptation law as a nonlinear function of the system’s classical error and its normalized acceleration. The proposed fuzzy system utilizes the knowledge of the system’s relative rate to execute better self-regulation of the adaptation rates, which in turn, flexibly steers the adaptability and response speed of the controller as the error conditions change. The propositions above are validated by performing tailored hardware experiments on a low-power DC–DC buck converter prototype. The experimental results validate the improved reference tracking and disturbance rejection ability of the proposed control law compared to the fixed PID controller.
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Amiri, Farhad, Mohsen Eskandari, and Mohammad Hassan Moradi. "Improved Load Frequency Control in Power Systems Hosting Wind Turbines by an Augmented Fractional Order PID Controller Optimized by the Powerful Owl Search Algorithm." Algorithms 16, no. 12 (2023): 539. http://dx.doi.org/10.3390/a16120539.
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The penetration of intermittent wind turbines in power systems imposes challenges to frequency stability. In this light, a new control method is presented in this paper by proposing a modified fractional order proportional integral derivative (FOPID) controller. This method focuses on the coordinated control of the load-frequency control (LFC) and superconducting magnetic energy storage (SMES) using a cascaded FOPD–FOPID controller. To improve the performance of the FOPD–FOPID controller, the developed owl search algorithm (DOSA) is used to optimize its parameters. The proposed control method is compared with several other methods, including LFC and SMES based on the robust controller, LFC and SMES based on the Moth swarm algorithm (MSA)–PID controller, LFC based on the MSA–PID controller with SMES, and LFC based on the MSA–PID controller without SMES in four scenarios. The results demonstrate the superior performance of the proposed method compared to the other mentioned methods. The proposed method is robust against load disturbances, disturbances caused by wind turbines, and system parameter uncertainties. The method suggested is characterized by its resilience in addressing the challenges posed by load disturbances, disruptions arising from wind turbines, and uncertainties surrounding system parameters.
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Jonnalagadda, Vimala Kumari, Vinodh Kumar Elumalai, and Shantanu Agrawal. "Current cycle feedback iterative learning control for tracking control of magnetic levitation system." Transactions of the Institute of Measurement and Control 42, no. 3 (2019): 543–50. http://dx.doi.org/10.1177/0142331219877052.
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This paper presents the current cycle feedback iterative learning control (CCF-ILC) augmented with the modified proportional integral derivative (PID) controller to improve the trajectory tracking and robustness of magnetic levitation (maglev) system. Motivated by the need to enhance the point to point control of maglev technology, which is widely used in several industrial applications ranging from photolithography to vibration control, we present a novel CCF-ILC framework using plant inversion technique. Modulating the control signal based on the current tracking error, CCF-ILC reduces the dependency on accurate plant model and significantly improves the robustness of the closed loop system by synthesizing the causal filters to counteract the effect of model uncertainty. To assess the stability, we present a maximum singular value based criterion for asymptotic stability of linear iterative system controlled using CCF-ILC. In addition, we prove the monotonic convergence of output sequence in the neighbourhood of reference trajectory. Finally, the proposed control framework is experimentally validated on a benchmark magnetic levitation system through hardware in loop (HIL) testing. Experimental results substantiate that synthesizing CCF-ILC with the feedback controller can significantly improve the trajectory tracking and robustness characteristics of maglev system.
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Bayrak, Abdurrahman, Handan Gürsoy, and Mehmet Önder Efe. "A novel robust fuzzy control of an uncertain system." Transactions of the Institute of Measurement and Control 39, no. 3 (2016): 324–33. http://dx.doi.org/10.1177/0142331216668394.
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This paper presents a robust control method combining the conventional proportional–integral–derivative (PID) scheme and the sliding mode fuzzy control scheme for a second-order non-linear system having uncertainties in the system dynamics. The goal of the proposed scheme is to force the response of the uncertain plant to follow that of the nominal model. The first phase of the design approach is to obtain a nominal PID controller for the nominal plant model. The poor performance of the sole PID scheme on the uncertain non-linear system motivates the proposal of the technique discussed here. To compensate for the deficiencies in the unit step response of the uncertain system, a fuzzy compensation scheme based on sliding mode control (SMC) is proposed and the PID loop is augmented by the proposed approach. It is shown that the performance with the proposed scheme is better than the sole PID-based control system. With the proposed technique, the response of the uncertain system converges to of the nominal system with admissible controller outputs. Furthermore, simulation results show that the proposed method produces consistent results even with noisy measurements.
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Li, Qunyi, Jintan Wang, Hezhe Zhang, Wei Zhao, and Li Chen. "Dynamic Coupling and Intelligent Control of Offshore Floating Wind Power Platforms." Energy & System 4, no. 1 (2024): 73–85. https://doi.org/10.71070/es.v4i1.23.
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This study delves into the dynamic coupling and intelligent control of offshore floating wind power platforms, leveraging a synergistic approach of field measurements and numerical simulations. Data were sourced from an operational platform in the North Sea and augmented with high-fidelity computational models developed using ANSYS AQWA. The research methodology encompassed data preprocessing, dynamic coupling analysis, intelligent control system design, and performance evaluation. The interaction between environmental forces (wind, waves, and currents) and the platform’s response (heave, pitch, and roll) was scrutinized through a coupled dynamic model. An intelligent control system, integrating a Proportional-Integral-Derivative (PID) controller with a fuzzy logic system, was devised to mitigate the platform’s motion. Performance metrics, including Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Stability Index (SI), revealed substantial enhancements with the intelligent control system, achieving reductions in RMSE and MAE by up to 50% and an increase in SI by up to 25%. These findings highlight the efficacy of the proposed control strategy in bolstering stability and diminishing the dynamic response of offshore floating wind power platforms under diverse environmental conditions.
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Tao, Xiangfei, Kailei Liu, and Jing Yang. "Neural Network and Generalized Extended State Observer Sliding Mode Control of Hydraulic Cylinder Position in the Independent Metering Control System with Digital Valves." Actuators 14, no. 5 (2025): 221. https://doi.org/10.3390/act14050221.
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The independent metering control system is renowned for its ability to independently regulate the flow and pressure of various actuators, achieving high efficiency and energy savings in hydraulic systems. The high-speed digital valve is known for its fast response to control signals and precise fluid control. However, challenges such as jitter in the position control of hydraulic cylinders, unknown dead zone nonlinearity, and time variance in electro-hydraulic proportional systems necessitate further investigation. To address these issues, this study initially establishes an independent metering control system with digital valves. Based on the state space equation and Lyapunov stability judgment conditions, a high-order sliding mode controller is designed. In addition, a radial basis function (RBF) neural network is constructed to approximate uncertainties arising from the modeling process, the accuracy error indicator uses Mean Absolute Error (MAE), and a finite time generalized extended state observer (GESO) is introduced to conduct online disturbance observation for the external disturbances present within the control system. Consequently, a variable structure high-order sliding mode control strategy, augmented by RBF neural networks and finite time generalized extended state observer (RBF-GESO-SMC), is proposed. Finally, simulations and experimental verification are performed, followed by a comprehensive analysis of the experimental results. Compared with the sliding mode control (SMC), the RBF-GESO-SMC diminishes the displacement-tracking control accuracy error by 63.7%. Compared with traditional Proportional-Integral-Derivative (PID) control, it reduces the displacement-tracking control accuracy error by 78.1%. The results indicate that, through the comparison with SMC and PID control, RBF-GESO-SMC exerts significant influence on the improvement of position accuracy, anti-interference ability, transient response performance, and stability.
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Sakib Arnob, Shadman, Adiba Sumaiya Khan, Rashed Shelim, and Mahmood Chowdhury. "Safe sailing: GSM and GPS controlled autonomous boat with overweight detection and obstacle avoidance." Indonesian Journal of Electrical Engineering and Computer Science 14, no. 2 (2019): 715. http://dx.doi.org/10.11591/ijeecs.v14.i2.pp715-724.
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<span>This paper aims to save thousands of lives by proposing a novel technique of ensuring the complete safety of medium-sized aquatic vehicles using innovative ideas as well as augmented adaptations of myriad existing technologies. The proposed system incorporates a warning and danger level detection circuit using transistors for switching purposes when the vehicles are overloaded, and a Global System for Mobile (GSM) based module so that the control room can receive alerts and control the engines of such vehicles centrally. A system for detecting and avoiding obstacles is made using ultrasonic radar with ultrasonic transducer JSN SR04t mounted on top of SG90 servo arm which rotates to detect any obstacles. When an obstacle is detected, two other ultrasonic sensors SR-04 gets activated which are placed on two sides of the aquatic vehicle and the ultrasonic transducer becomes fixed on the exact centre. All the three sensors work together to find a free path for the boat to travel. If there is no free path, the boat will stop and wait for the paths to get cleared. The location of the vehicle is tracked by the Global Positioning System (GPS) and a Proportional-Integral-Derivative (PID) controller has been included along with a system which uses values from the GPS module to come back to its original path if it deviates from the original path when avoiding obstacles. A barcode system has been added where it keeps a count on the passengers. The tickets for the vehicle will have barcodes on them which will let the passengers in only if the barcode matches. This is used mainly to keep track of how many people are boarding the vehicle and to prevent those without tickets from boarding.</span>
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Sabatini, Roberto, Leopoldo Rodríguez, Anish Kaharkar, Celia Bartel, Tesheen Shaid, and David Zammit-Mangion. "LOW-COST NAVIGATION AND GUIDANCE SYSTEMS FOR UNMANNED AERIAL VEHICLES — PART 2: ATTITUDE DETERMINATION AND CONTROL." Annual of Navigation 20, no. 1 (2013): 97–126. http://dx.doi.org/10.2478/aon-2013-0008.
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ABSTRACT This paper presents the second part of the research activity performed by Cranfield University to assess the potential of low-cost navigation sensors for Unmanned Aerial Vehicles (UAVs). This part focuses on carrier-phase Global Navigation Satellite Systems (GNSS) for attitude determination and control of small to medium size UAVs. Recursive optimal estimation algorithms were developed for combining multiple attitude measurements obtained from different observation points (i.e., antenna locations), and their efficiencies were tested in various dynamic conditions. The proposed algorithms converged rapidly and produced the required output even during high dynamics manoeuvres. Results of theoretical performance analysis and simulation activities are presented in this paper, with emphasis on the advantages of the GNSS interferometric approach in UAV applications (i.e., low cost, high data-rate, low volume/weight, low signal processing requirements, etc.). The simulation activities focussed on the AEROSONDE UAV platform and considered the possible augmentation provided by interferometric GNSS techniques to a low-cost and low-weight/volume integrated navigation system (presented in the first part of this series) which employed a Vision-Based Navigation (VBN) system, a Micro-Electro-Mechanical Sensor (MEMS) based Inertial Measurement Unit (IMU) and code-range GNSS (i.e., GPS and GALILEO) for position and velocity computations. The integrated VBN-IMU-GNSS (VIG) system was augmented using the inteferometric GNSS Attitude Determination (GAD) sensor data and a comparison of the performance achieved with the VIG and VIG/GAD integrated Navigation and Guidance Systems (NGS) is presented in this paper. Finally, the data provided by these NGS are used to optimise the design of a hybrid controller employing Fuzzy Logic and Proportional-Integral-Derivative (PID) techniques for the AEROSONDE UAV.
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Nguyen, Ngoc P., and Phongsaen Pitakwachara. "Integral terminal sliding mode fault tolerant control of quadcopter UAV systems." Scientific Reports 14, no. 1 (2024). http://dx.doi.org/10.1038/s41598-024-61273-2.
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AbstractThe article presents an active fault-tolerant control scheme with an integral terminal sliding mode controller for the UAV systems. This scheme effectively addresses saturation issues, disturbances, and sensor and actuator faults. Initially, the quadcopter UAV's model is represented in state space form. Subsequently, an augmented system incorporating auxiliary states from sensor faults is developed. An adaptive sliding mode observer is proposed for estimating the actuator and sensor faults. The integral terminal sliding mode fault-tolerant control, designed for altitude and attitude regulation, relies on fault estimation data. In contrast, a cascade proportional-integral-derivative (PID) controller is employed for position control. Simulation results demonstrate the superiority of the proposed method over existing control algorithms.
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Kistyarev, Mikhail, and Xinhua Wang. "Unmanned F/A-18 Aircraft Landing Control on Aircraft Carrier in Adverse Conditions." Aerotecnica Missili & Spazio, February 12, 2025. https://doi.org/10.1007/s42496-025-00249-5.
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Abstract Carrier landing of aircrafts is a challenge for control due to the existence of nonlinear wind disturbances and the requirements of changing reference trajectories. In this paper, a robust landing control system is presented for carrier landing of unmanned F/A-18 aircraft. In the control system, an augmented observer is applied to estimate the combined disturbances in the pitch dynamics of F/A-18 aircraft during carrier landing. Therefore, the control performance is improved through the control compensations from these estimations. Additionally, the controllers are designed to regulate the velocity, rate of descent and vertical position. A full model, including the nonlinear flight dynamics, controller, carrier deck motion, wind and measurement noise, is constructed numerically and implemented in software. Combining the observer with a proportional-derivative (PD) control, the proposed pitch control shows the better transient characteristics and stronger robustness than a proportional-integral-derivative (PID) controller. The simulations verify that the designed control system can make the aircraft quickly track a time-varying reference despite the existence of nonlinear disturbances and noise.
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Ekinci, Serdar, Davut Izci, Laith Abualigah, Abdelazim G. Hussien, Cuong-Le Thanh, and Samir Khatir. "Revolutionizing Vehicle Cruise Control: An Elite Opposition-Based Pattern Search Mechanism Augmented INFO Algorithm for Enhanced Controller Design." International Journal of Computational Intelligence Systems 16, no. 1 (2023). http://dx.doi.org/10.1007/s44196-023-00304-8.
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AbstractThis paper presents a groundbreaking approach to enhance the performance of a vehicle cruise control system—a crucial aspect of road safety. The work offers two key contributions. Firstly, a state-of-the-art metaheuristic algorithm is proposed by augmenting the performance of the weighted mean of vectors (INFO) algorithm using pattern search and elite opposition-based learning mechanisms. The resulting boosted INFO (b-INFO) algorithm surpasses the original INFO, marine predators, and gravitational search algorithms in terms of performance on benchmark functions, including unimodal, multimodal, and fixed-dimensional multimodal functions. Secondly, a novel proportional, fractional order integral, derivative plus double derivative with filter ($$P{I}^{\lambda }DN{D}^{2}{N}^{2}$$ P I λ D N D 2 N 2 ) controller is proposed as a more efficient control structure for vehicle cruise control systems. An objective function is utilized to determine the optimal values for the controller parameters, and the proposed method's performance is compared against a range of recent approaches. Results demonstrate that the b-INFO algorithm-based $$P{I}^{\lambda }DN{D}^{2}{N}^{2}$$ P I λ D N D 2 N 2 controller is the most efficient and superior method for controlling a vehicle cruise control system. Moreover, this work represents the first report of a $$P{I}^{\lambda }DN{D}^{2}{N}^{2}$$ P I λ D N D 2 N 2 controller’s implementation for vehicle cruise control systems, underscoring the novelty and significance of this research. The proposed method's exceptional ability is further confirmed by comparisons with the genetic algorithm, ant lion optimizer, atom search optimizer, arithmetic optimization algorithm, slime mold algorithm, Lévy flight distribution algorithm, manta ray foraging optimization, and hunger games search-based proportional–integral–derivative (PID), along with Harris hawks optimization-based PID and fractional order PID controllers. This work marks a remarkable milestone toward safer and more efficient vehicle cruise control systems.
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Das, Dipjyoti, Sudipta Chakraborty, and G. Lloyds Raja. "Enhanced dual-DOF PI-PD control of integrating-type chemical processes." International Journal of Chemical Reactor Engineering, December 12, 2022. http://dx.doi.org/10.1515/ijcre-2022-0156.
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Abstract A dual-degree of freedom (dual-DOF) propor-tional-integral proportional-derivative (PI-PD) controller is developed for integrating-type chemical processes with delay. The interior-loop PD controller is designed based on user-defined gain and phase margin. For designing the external-loop PI controller, the moment-matching method is augmented with maximum sensitivity specifications. The suggested design is suitable for chemical processes like continuously stirred tank reactors, boiler steam drums, heat exchangers and distillation columns. Using benchmark models of the aforementioned processes, the closed-loop system outputs and control signals are compared to vindicate the primacy of the suggested dual-DOF PI-PD controller. To study the performance-robustness trade-off of this design, rigorous perturbation analysis is also carried out. The performance improvement achieved by the suggested dual-DOF PI-PD controller is also quantitatively compared with contemporary works.
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He, Liqiang, Siyuan Li, Jiatong Du, and Haibo Zhang. "Research on turboprop engine control method based on linear parameter varying model." International Journal of Turbo & Jet-Engines, January 30, 2023. http://dx.doi.org/10.1515/tjj-2022-0075.
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Abstract Starting from a component-level nonlinear model of a turboprop engine, the high-pressure turbine speed and power turbine speed output data at six steady-state operating points are linearized and fitted, and a turboprop engine state variable model is established. Based on these state variable models, the Proportional Integral Derivative (PID) control method, the augmented Linear Quadratic Regulator (LQR) control method and the Linear Quadratic Gaussian/Loop Transfer Recover (LQG/LTR) control method are used to design the controllers respectively, and the relative converted speed of the high-pressure turbine is selected as the scheduling parameter of the Linear Parameter Varying (LPV) model, and the controller is called to control the turboprop engine’s non-linear speed. Linear model for large envelope control. Finally, the control effects of the above three control methods are compared and analyzed, and their advantages and disadvantages are compared. The simulation results show that the LPV controller designed based on the LQG/LTR method is more effective than the controllers designed by the other two control methods on the nonlinear turboprop model.
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Sir Elkhatem, Aisha, Seref Naci Engin, and Zainab Malik. "New FOPID Control Design for Flight Dynamics With Special Phenomena." Optimal Control Applications and Methods, May 15, 2025. https://doi.org/10.1002/oca.3293.
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ABSTRACTThe design of a flight control system (FCS) for aircraft altitude change dynamics presents significant challenges due to the inherent non‐minimum phase (NMP) behavior. This behavior leads to undesirable initial undershoot responses, imposing significant limitations on internal stability and severely restricting the performance and robustness of directly applying conventional control methods. Despite the widespread use of proportional–integral–derivative (PID) controllers in industrial applications, their robustness, performance, and disturbance rejection deteriorate when applied to systems exhibiting NMP characteristics. This paper highlights the practical importance of upgrading PID‐based controllers for flight dynamics with NMP behavior by addressing these challenges, with a particular focus on tracking and stability issues under direct feedback control. To overcome these limitations, we propose a modified control architecture incorporating a fractional‐order PID (FOPID) controller, augmented with a fractional‐order derivative filtering component (FD). This design aims to enhance transient response, noise immunity, and adaptability without adding significant complexity. The control problem is framed as a single‐objective optimization task, where the Particle Swarm Optimization (PSO) algorithm is used to simultaneously tune the proposed controller gains, minimizing the error between the actual and desired altitude commands. The performance of the proposed controller was compared to traditional PID and FOPID controllers through both time and frequency domain analyses, under scenarios involving parametric uncertainty and 50% and 80% loss of effectiveness in the actuator (elevator) fault. The performance evaluation was based on transient response criteria, while robustness was assessed in terms of delay, phase, and gain margins. The simulation results show that under nominal flight conditions, the proposed controller significantly outperforms conventional FOPID controllers, reducing the percent overshoot from 52% to 2% for the Integral Absolute Error (IAE), from 44% to 2% for the Integral Time Squared Error (ITSE), and from 60% to 3% for the Integral Time Absolute Error (ITAE) performance metrics. The robustness analysis reveals that even under extreme conditions, such as system uncertainties, 50% and 80% actuator loss, the proposed controller maintains stability. Across these cases, it achieves a minimum phase margin of 158° and a gain margin of 13.3 dB, in contrast to the 27.8° and 16.4 dB observed with conventional controllers. These findings underscore the controller's efficacy in providing reliable and robust altitude control in real‐world flight conditions, even under significant actuator degradation and system uncertainties.
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Donati, Giovanni, Massimiliano Ortiz Neri, Marco Mugnaini, Michele Basso, and Jerzy T. Sawicki. "Low-order MIMO controller for turbomachinery supported by active magnetic bearings." Journal of Vibration and Control, February 3, 2025. https://doi.org/10.1177/10775463251317667.
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In industry, the operation of turbomachinery supported by active magnetic bearings (AMBs) requires a robust and simple controller to meet increased performance requirements and stringent regulations. This study proposes an innovative low-order Multiple-Input Multiple-Output (MIMO) controller. Its structure is derived from the decentralized augmented Proportional-Integral-Derivative (PID) controller, enhanced with fixed terms in the skew-diagonals of the controller matrix. The resulting controller couples the information acquired by the AMB sensors on the same control axis to enhance the overall performance. The parameters of the new MIMO structure are tuned using a model-based procedure that exploits a non-smooth optimization algorithm, with the rotor model adjusted on experimental measurements to represent the real dynamics of the system. The novel controller performance is evaluated through two case studies: first, an expander-compressor system; second, a centrifugal turbo compressor designed for oil and gas applications, facing challenges associated with the observability and controllability of the second bending mode. The performance is then compared with that obtained using a decentralized augmented PID controller whose parameters have been tuned with the same non-smooth optimization algorithm. The new controller demonstrates a significant reduction in vibration caused by rotor bending modes. For example, in the analyzed case studies, unbalance responses were reduced by up to a factor of 10. Moreover, the proposed controller increases robustness compared to the decentralized case, as demonstrated by the second case study where controllability and observability issues are addressed.
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Yuan, Yuan, X. Chen, and J. Tang. "Disturbance Observer-Based Pitch Control of Wind Turbines for Enhanced Speed Regulation." Journal of Dynamic Systems, Measurement, and Control 139, no. 7 (2017). http://dx.doi.org/10.1115/1.4035741.
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Time-varying unknown wind disturbances influence significantly the dynamics of wind turbines. In this research, we formulate a disturbance observer (DOB) structure that is added to a proportional-integral-derivative (PID) feedback controller, aiming at asymptotically rejecting disturbances to wind turbines at above-rated wind speeds. Specifically, our objective is to maintain a constant output power and achieve better generator speed regulation when a wind turbine is operated under time-varying and turbulent wind conditions. The fundamental idea of DOB control is to conduct internal model-based observation and cancelation of disturbances directly using an inner feedback control loop. While the outer-loop PID controller provides the basic capability of suppressing disturbance effects with guaranteed stability, the inner-loop disturbance observer is designed to yield further disturbance rejection in the low frequency region. The DOB controller can be built as an on–off loop, that is, independent of the original control loop, which makes it easy to be implemented and validated in existing wind turbines. The proposed algorithm is applied to both linearized and nonlinear National Renewable Energy Laboratory (NREL) offshore 5-MW baseline wind turbine models. In order to deal with the mismatch between the linearized model and the nonlinear turbine, an extra compensator is proposed to enhance the robustness of augmented controller. The application of the augmented DOB pitch controller demonstrates enhanced power and speed regulations in the above-rated region for both linearized and nonlinear plant models.
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Ta, Thi-Na, Yunn-Lin Hwang, and Jeng-Haur Horng. "A Multidisciplinary Approach for Optimization Design of CNC Machine Tools." International Journal of Computational Methods, March 20, 2021, 2150028. http://dx.doi.org/10.1142/s0219876221500286.
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The main objective of this research is to propose a multidisciplinary approach for the development and design of Computer Numerical Control (CNC) machine tools using numerical optimization methods combined Multi-Body Dynamic (MBD) analysis and to control design co-simulation. Metamodels based Sequential Approximate Optimization (SAO) for the co-simulation optimization problems are developed. The metamodels are constructed as approximate models for exact dynamic analysis responses by using simultaneous Kriging metamodeling method. SAO problems for single objective and multi-objective optimization designs are carried out based on the augmented Lagrange multiplier (ALM) method. An application of the proposed method on optimizing Proportional-Integral-Derivative (P-I-D) coefficients of PID controllers of a CNC machine tool model is performed to demonstrate the usefulness of integrating different research methods in numerical simulation. Therefore, this work overcomes a difficult task in tuning the PID controller which requires extensive experience and understandings of research and development (R&D) engineers. Moreover, the optimal PID controllers obtained by the multidisciplinary approach can help to increase the contouring accuracy of the CNC machine tools.
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Maghami, Ali, and Matt Khoshdarregi. "Vision-based target localization and online error correction for high-precision robotic drilling." Robotica, October 21, 2024, 1–25. http://dx.doi.org/10.1017/s0263574724001255.
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Abstract This article presents a detailed examination of circular target localization techniques for measuring robot pose and performing online pose correction. The investigated target localization methods include centroiding, ellipse fitting with point data and gradient information, and ellipse fitting methods with augmented and corrected input data. The performance of each method is evaluated in terms of accuracy and precision of measurements through experimental comparison with a laser tracker. This study provides technical and practical insights for selecting an appropriate target localization method in robotic applications. It also introduces a vision-based solution for robot relative error correction, comprising the calibration procedure and a closed-loop control with a proportional–integral-derivative controller for pose correction. Results show enhanced accuracy in robot positioning relative to workpiece, highlighting the effectiveness of the proposed solution in robotic drilling applications.
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Silas, Manjusha, and Surekha Bhusnur. "GWO based Robust Stabilization of DC Motor Fractional Order Speed Control System with Interval Coefficients." International Journal of Vehicle Structures and Systems 15, no. 3 (2023). http://dx.doi.org/10.4273/ijvss.15.3.14.
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Robust stability analysis (RSA) is of significant concern for the robust behaviour of real-world control system applications. A stabilization strategy that assures stability and exhibits robust performance for a specified limit of system perturbations is necessary. This article presents an optimal robust stabilization method for a closed loop fractional order proportional integral derivative (FOPI^λD^µ) system involving DC motor with interval parametric uncertainty. To determine the optimum value of parameters for a FOPI^λD^µ controller to control the speed of a DC motor, Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), Nelder-Mead (NM), Jaya and Whale Optimizer Algorithm (WOA) are applied with the same objective function involving ITAE criterion. FOPI^λD^µ offers two additional tuning parameters unlike a nominal PID controller and hence the former gives more flexibility in controller design than the latter in terms of transient response. The FOPID controller provides a faster closed-loop output augmented with improved robust properties of the system. Despite inherent non-linearities and time variation in system parameters, FOPI^λD^µ controllers depict enhanced performance. Using the concept of conformal mapping, robust stability analysis of fractional order polynomials is done with uncertain interval structure using Vertex and Edge theorem. Based on the value set, this paper demonstrates numerical and graphical optimal robust stability analysis of a system with variations observed in five parameters, considering the minimum argument root of the polynomial of the aforementioned closed-loop system.
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Chen, Qianhui. "Design of Human–Computer Interaction Gesture Recognition System Based on a Flexible Biosensor." International Journal of Computational Intelligence Systems 17, no. 1 (2024). http://dx.doi.org/10.1007/s44196-024-00588-4.
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AbstractThe continuous development of high-speed Internet technology has made the application of robots increasingly widespread. Current robots and human–computer interaction systems mostly use rigid materials, such as metals and semiconductors, which have limitations in terms of deformability and flexibility. In addition, the biocompatibility and user comfort of these materials are also an issue. Therefore, research into new flexible biosensors is essential to improve the flexibility, comfort, and interactivity of these systems. This research will select polymer hydrogel as the electrode material of the sensor and polydimethylsiloxane as the base material of the sensor to design a resistance flexible biosensor to solve the poor flexibility. The research will use a template-matching method to verify the feasibility of gesture recognition of the flexible sensor. The remote control system of the robot finger is designed by a proportional-integral differential controller tuned by aradial basis function neural network. The feasibility of the research system is verified by simulation and scene experiments. The flexible sensor studied and prepared had a sensitivity of 0.7269, a tensile limit of 300%, and a thickness of 0.16 mm, showing good sensitivity and stability. The recognition accuracy of the sensor designed in the study was 92.8%, which was 8.1% higher than that of the data glove. Compared with traditional proportional-integral derivative (PID) controllers, the improved controller system error was within 10 to 3 rad, which had better adaptability and stability. Key information includes the design method of the flexible biosensor, its high sensitivity and stability under multiple stretches, and the proposal and validation of a new RBFNN–PID control model. These results showed that using this new sensor and control model significantly improved the control accuracy of mechanical fingers and the effect of gesture recognition. These results have important implications for the development of more advanced human–computer interaction systems. They not only improve the performance and reliability of the system, but also improve the user's interactive experience. These technologies are particularly promising in the fields of prosthetics for disabled people, advanced game controllers, and remotely controlled robots operating in hazardous environments. The research results are expected to lead to the development of advanced prosthetics, augmented reality devices, advanced game controllers, and automated robots. The main contribution of the research is to design a resistive flexible biosensor, which improves the traditional sensor's poor flexibility and large size and improves the sensor's ability to sense small changes. Future research may focus on further improving the sensor's long-term stability and performance under a variety of environmental conditions. In addition, commercializing these technologies and making them universal is also an important direction for the future.
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Jarroux, Clément, Jarir Mahfoud, Benjamin Defoy, and Thomas Alban. "Stability of Rotating Machinery Supported on Active Magnetic Bearings Subjected to Base Excitation." Journal of Vibration and Acoustics 142, no. 3 (2020). http://dx.doi.org/10.1115/1.4046124.
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Abstract The stability of rotating machinery is a major challenge for the floating production storage and offloading (FPSO) units such as steam turbines or centrifugal compressors. The use of active magnetic bearings (AMBs) in turbomachines enables high operating speeds, active mechatronic system for the diagnostics, and the control and enables downsizing of the whole installation footprint. In case of strong base motions, the rotor can contact its touchdown bearings (TDBs) which are used as emergency and landing bearings. The aim of this study is to assess the stability of a rotating machine supported on AMBs during severe foundation excitation. The combined effect of unbalance forces, base motion excitation, and contact non-linearity on a rotor–AMB system response is analyzed focusing on the capacity of an augmented proportional-integral-derivative controller to maintain the system stable. An academic scale test rig was used for the experimental investigations. The controller was efficient and able to maintain the system stable during and after the application of the excitation, but the dynamic capacity of the AMBs was largely oversized with respect to the studied system. In order to check the capacity of the AMBs, when they are designed as a function of the rotor weight and expected excitation, numerical simulations were carried out (downsized). A finite element (FE) model was developed to model the on-board rotor–AMB system. Predicted and measured responses due to impulse excitation applied on the foundations were compared. The capacity of the controller to maintain the system stability is then discussed.
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de Oliveira, Éverton L., Décio C. Donha, Agenor de T Fleury, and Ettore A. de Barros. "Station-keeping of a ROV under wave disturbance: Modeling and control design." Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, September 2, 2022, 147509022211166. http://dx.doi.org/10.1177/14750902221116673.
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Remotely Operated Vehicles (ROVs) working close to the sea surface are subjected to wave disturbances that affect their positioning. To treat this problem, we present a control scheme for the dynamic positioning of ROVs under wave disturbances and at low operation depths. The approach is composed of an Augmented Wave Filter (AWF) based on the Extended Kalman Filter (EKF) algorithm and an Adaptive-Model Predictive Control (A-MPC). The filter provides the optimal motion states and wave height estimation to the A-MPC, which calculates the control efforts based on the receding horizon approach. The scheme is tested through numerical simulations on the depth control of the Mandi II-ROV at the diving plane. The results are compared to those of a standard Proportional-Integral-Derivative (PID) controller. To perform realistic simulations, a detailed mathematical model is presented, considering the rigid body-motion, hydrodynamic and hydrostatic forces, thrusters dynamics, and onboard sensor measurements. The simulations are performed for different scenarios, considering the dynamic positioning in still waters and the station-keeping under wave disturbances for significant heights of 1 and 2 m. The controller robustness to parameter variation is assessed by using Monte-Carlo simulation. Results have shown improved performance for the A-MPC in terms of positioning errors, motion oscillations, and drift attenuation in comparison to a PID controller. The Monte-Carlo simulation reveals enhanced robustness to the A-MPC, which is associated with the greater variance for the control forces. Also, the filter performed very well in all the tests, producing an accurate estimate of the wave-induced height and providing an off-set free control.
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Kumar, Rajnish, Chinmay Bera, and Amitesh Kumar. "Optimization of BLDC-based electric vehicles: vehicle dynamics modelling through dual-motor approach and designing a novel augmented TLBO algorithm for PID control." Engineering Research Express, April 30, 2024. http://dx.doi.org/10.1088/2631-8695/ad45b3.
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Abstract Sample The work primarily focuses on increasing the efficiency of EV drive in electric two-wheeler by working on several aspects, such as modulating the vehicle's design, optimizing the control strategy, and increasing the speed range using a dual-motor approach. The dynamics of electric two-wheeler have been discussed with a mathematical vehicle model and further tuning of several aspects. Besides, this paper also introduces a novel Augmented Teaching and Learning based Optimization (ATLBO) technique designed exclusively to control BLDC motors for the electric two-wheeler vehicle. Besides, the designed technique has been implemented for the widely used commercial e-bike of Hero Company. Therefore, an analysis has been performed to increase the vehicle's speed range using a dual motor, from 45 km/hr to 62 km/hr, proving to be a viable alternative to a single motor generally used in an electric bike. ATLBO technique has been designed against a conventional TLBO to optimize the proportional-integral-derivative (PID) controller for the speed control of a linear brushless DC (BLDC) motor. Furthermore, the literature has validated the merits of the presented novel control technique. The only disadvantage of using a dual motor is the initial cost, but the overall cost is moderated in the long-term usage for its augmented performance parameters. The performance parameters of the above technique are analyzed against other optimization techniques like conventional Teaching and Learning based optimization (TLBO), Particle Swarm Optimization (PSO). MATLAB/Simulink models the brushless DC motor and implements ATLBO, TLBO, and PSO algorithms. It has been found that the response obtained from ATLBO is comparatively much faster than other optimization techniques, which supports the motor for quick acceleration as well as more efficient in improving the step response characteristics such as rise time, settling time, and steady-state error in the speed control of a linear BLDC motor.&#xD;
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Filo, Maurice, Sant Kumar, and Mustafa Khammash. "A hierarchy of biomolecular proportional-integral-derivative feedback controllers for robust perfect adaptation and dynamic performance." Nature Communications 13, no. 1 (2022). http://dx.doi.org/10.1038/s41467-022-29640-7.
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AbstractProportional-Integral-Derivative (PID) feedback controllers are the most widely used controllers in industry. Recently, the design of molecular PID-controllers has been identified as an important goal for synthetic biology and the field of cybergenetics. In this paper, we consider the realization of PID-controllers via biomolecular reactions. We propose an array of topologies offering a compromise between simplicity and high performance. We first demonstrate that different biomolecular PI-controllers exhibit different performance-enhancing capabilities. Next, we introduce several derivative controllers based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop, which can be augmented by PI-components to yield PID-controllers. We demonstrate that PID-controllers can enhance stability and dynamic performance, and can also reduce stochastic noise. Finally, we provide an experimental demonstration using a hybrid setup where in silico PID-controllers regulate a genetic circuit in single yeast cells.
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Xu, Bin, Adamu Yebi, Dhruvang Rathod, Simona Onori, Zoran Filipi, and Mark Hoffman. "Experimental Validation of Nonlinear Model Predictive Control for a Heavy-Duty Diesel Engine Waste Heat Recovery System." Journal of Dynamic Systems, Measurement, and Control 142, no. 5 (2020). http://dx.doi.org/10.1115/1.4046152.
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Abstract This paper discusses an experimental validation of a real-time augmented control scheme for an organic Rankine cycle (ORC) waste heat recovery (WHR) system. A nonlinear model predictive control (NMPC) is designed to regulate the working fluid vapor temperature after the evaporator. The NMPC utilizes a six-state reduced order moving boundary (MB) evaporator model. The state estimator is constructed using an extended Kalman filter (EKF) given the working fluid outlet vapor temperature and exhaust gas outlet temperature as measurements. Working fluid evaporation pressure is controlled by an external proportional-integral-derivative (PID) control loop. The experimental validation first compares the performance of the augmented control scheme with that of a traditional multiple loop PID control with a feedforward term over an engine transient. The experimental study shows that the augmented control scheme outperforms the baseline multiloop PID control in both terms tracking error and settling time during transient engine operation. The performance of the augmented control scheme is further validated over three additional transient conditions with alterations to both the engine transient and the working fluid reference temperature. The NMPC validation shows that the working fluid vapor temperature can be controlled within 1% error margin relative to the targeted reference.