MTN optimal control of MIMO non-affine nonlinear time-varying discrete systems for tracking only by output feedback |
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| Institution: | 1. Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing 210096, China;2. School of Automation, Southeast University, Nanjing 210096, China;1. College of Science, Liaoning University of Technology, Jinzhou 121001, PR of China;2. College of Information Science and Engineering, State Key Laboratory of Synthetical Automation of Process Industries, Northeastern University, Shenyang 110819, PR China;1. Department of Electrical Engineering, Jordan University of Science and Technology, Irbid 22110, Jordan;2. Electrical Power & Machines Department, High Institute of Engineering, El Shorouk Academy, Cairo, Egypt;3. Electrical Power and Energy Department, Military Technical College, Cairo, Egypt;4. Faculty of Engineering and Technology, Future University in Egypt, Cairo, Egypt;5. Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH 43210, United States;6. Department of Electrical Engineering, COMSATS University Isamabad, Islamabad, Pakistan;1. Department of Information and Communication Engineering, DGIST, Daegu 42988, Republic of Korea;2. Department of Electrical Engineering, Soongsil University, Seoul 06978, Republic of Korea;1. School of Automation, Central South University, Changsha 410083, China;2. School of Automation, China University of Geosciences, Wuhan 430074, China;3. Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan 430074, China |
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| Abstract: | In practice, many controlled plants are equipped with MIMO non-affine nonlinear systems. The existing methods for tracking control of time-varying nonlinear systems mostly target the systems with special structures or focus only on the control based on neural networks which are unsuitable for real-time control due to their computation complexity. It is thus necessary to find a new approach to real-time tracking control of time-varying nonlinear systems. In this paper, a control scheme based on multi-dimensional Taylor network (MTN) is proposed to achieve the real-time output feedback tracking control of multi-input multi-output (MIMO) non-affine nonlinear time-varying discrete systems relative to the given reference signals with online training. A set of ideal output signals are selected by the given reference signals, the optimal control laws of the system relative to the selected ideal output signals are set by the minimum principle, and the corresponding optimal outputs are taken as the desired output signals. Then, the MTN controller (MTNC) is generated automatically to fit the optimal control laws, and the conjugate gradient (CG) method is employed to train the network parameters offline to obtain the initial parameters of MTNC for online learning. Addressing the time-varying characteristics of the system, the back-propagation (BP) algorithm is implemented to adjust the weight parameters of MTNC for its desired real-time output tracking control by the given reference signals, and the sufficient condition for the stability of the system is identified. Simulation results show that the proposed control scheme is effective and the actual output of the system tracks the given reference signals satisfactorily. |
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