Evolving an interval type-2 fuzzy PID controller for the redundant robotic manipulator |
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| Affiliation: | 1. Faculty of Information Technology, Ho Chi Minh City University of Technology, Vietnam;2. College of Electronics and Information Engineering, Sejong University, Seoul, Republic of Korea;3. University of Economics & Finance, Ho Chi Minh City, Vietnam;4. Division of Data Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam;5. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam;6. Key Laboratory of Machine Perception (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China;1. School of Information Technology & Mathematical Sciences, University of South Australia, SA 5001, Australia;2. School of Engineering, University of South Australia, SA 5001, Australia;3. Respiratory & Sleep Medicine, Women''s and Children''s Hospital, North Adelaide, SA 5006, Australia;4. Robinson Research Institute, Adelaide Medical School, University of Adelaide, SA 5005, Australia;1. Department of Computer Science & Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Amrita University, Bangalore, India;2. Department of Mathematics, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Amrita University, Bangalore, India;1. Montpellier Business School, 2300 avenue des Moulins, 34080 Montpellier, France;2. Fundvisory, 48 rue du Château Landon, 75010 Paris, France;1. LIRMM - 860, rue de Saint Priest, Montpellier, 34095, France;2. INRA - UMR IATE - 2, place Pierre Viala, Montpellier, 34060, France;3. UMR MIA-Paris, AgroParisTech, INRA, Université Paris-Saclay, Paris,75005, France;4. CIRAD - UMR TETIS - 500, rue J.F. Breton, Montpellier 34093, France;1. Department of Strategic Management and Marketing, Leicester Business School, De Montfort University, Hugh Aston Building, The Gateway, Leicester LE1 9BH, UK;2. HEC Management School, University of Liege, 4000 Liège, Belgium;3. Department of Systems Engineering, Faculty of Economics, Technical University of Ostrava, Sokolska t?. 33, 701 21 Ostrava 1, Ostrava, Czech Republic |
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| Abstract: | Robotic manipulators are a multi-input multi-output, dynamically coupled, highly time-varying, complex and highly nonlinear systems wherein the external disturbances, parameter variations, and random noise adversely affects the performance of the robotic system. Therefore, in order to deal with such complexities, however, an intriguing task for control researchers, these systems require an efficient and robust controller. In this paper, a novel application of genetic algorithms (GA) optimization approach to optimize the scaling factors of interval type-2 fuzzy proportional derivative plus integral (IT2FPD+I) controllers is proposed for 5-DOF redundant robot manipulator for trajectory tracking task. All five controllers' parameters are optimized simultaneously. Further, a procedure for selecting appropriate initial search space is also demonstrated. In order to make a fair comparison between different controllers, the tuning of each of the controllers' parameters is done with GA. This optimization technique uses the time domain optimal tuning while minimizing the fitness function as the sum of integral of multiplication of time with square error (ITSE) for each joint. To ascertain the effectiveness of IT2FPID controller, it is compared against type-1 fuzzy PID (T1FPID) and conventional PID controllers. Furthermore, robustness testing of developed IT2FPID controller for external disturbances, parameter variations, and random noise rejection is also investigated. Finally, the experimental study leads us to claim that our proposed controller can not only assure best trajectory tracking in joint and Cartesian space, but also improves the robustness of the systems for external disturbances, parameter variations, and random noise. |
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