An optimal adaptive robust PID controller subject to fuzzy rules and sliding modes for MIMO uncertain chaotic systems |
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| Affiliation: | 1. Department of Mechanical Engineering, Sirjan University of Technology, Sirjan, Iran;2. Department of Mechanical and Aerospace Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran;3. Department of Mechanical Engineering, The University of Texas at San Antonio, San Antonio, TX 78249, USA;1. Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia;2. Department of Computer Engineering, Hashtgerd Branch, Islamic Azad University, Alborz, Iran;1. IT4Innovations, V?B-Technical University of Ostrava, Ostrava, Czech Republic;2. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA;1. School of Computer Science, Laboratory of Cognitive Modeling and Algorithms, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China;2. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, China;1. Department of Mathematics, Faculty of Arts and Sciences, Eastern Mediterranean University, Famagusta, North Cyprus, Mersin-10, Turkey;2. Department of Computer Science and Information Technology, Faculty of Electrical Engineering and Information Technology, University of Oradea, Oradea, Romania;1. Department of Computational Intelligence, Faculty of Computer Science and Management Wroclaw, University of Science and Technology, Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland;2. Department of Systems and Computer Networks, Faculty of Electronics, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland;1. College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China;2. School of Mathematics, Thapar University, Patiala 147004, Punjab, India |
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| Abstract: | In this paper, an optimal adaptive robust PID controller based on fuzzy rules and sliding modes is introduced to present a general scheme to control MIMO uncertain chaotic nonlinear systems. In this control scheme, the gains of the PID controller are updated by using an adaptive mechanism, fuzzy rules, the gradient search method, and the chain rule of differentiation in order to minimize the sliding surfaces of sliding mode control. More precisely, sliding mode control is used as a supervisory controller to provide sufficient control inputs and guarantee the stability of the control approach. To ascertain the parameters of the proposed controller and avoid trial and error, the multi-objective genetic algorithm is employed to augment the performance of proposed controller. The chaotic system of a Duffing-Holmes oscillator and an industrial robotic manipulator are the case studies to evaluate the performance of the proposed control approach. The obtained results of this study regarding both systems are compared with the outcomes of two notable studies in the literature. The results and analysis prove the efficiency of the proposed controller with regard to MIMO uncertain systems having challenging external disturbances in terms of stability, minimum tracking error and optimal control inputs. |
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| Keywords: | Adaptive robust controller PID controller Sliding mode controller Multi-objective genetic algorithm Fuzzy rules MIMO uncertain chaotic systems Robot manipulator Duffing-Holmes oscillator |
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