International Journal of Control, Automation and Systems 2020; 18(2): 363-373
Published online August 19, 2019
https://doi.org/10.1007/s12555-019-0285-0
© The International Journal of Control, Automation, and Systems
In this paper, a novel adaptive fuzzy immune feedback reaching law (AFIFRL) based sliding mode control (SMC) strategy is proposed for uncertain nonlinear systems with time-varying disturbances. First, a nonlinear immune feedback reaching law (IFRL) inspired by biological immune feedback regulation mechanism is designed to alleviate chattering effect without losing the robustness against disturbances. Second, an improved IFRL is developed in a thin boundary layer to enhance tracking performance. Then, the applied fuzzy controller adjusts the boundary layer online to further improve control performance despite large system uncertainties and disturbances. Furthermore, an adaptive law is employed to estimate the unknown bound of uncertainties, which can effectively attenuate chattering and minimize control effort. The stability analysis is derived by Lyapunov stability theorem. Finally, numerical simulations are conducted to evidence the effectiveness and superiority of the proposed AFIFRL based SMC scheme.
Keywords Adaptive control, biological immune mechanisms, chattering elimination, fuzzy logic, immune feedback reaching law, sliding mode control.
International Journal of Control, Automation and Systems 2020; 18(2): 363-373
Published online February 1, 2020 https://doi.org/10.1007/s12555-019-0285-0
Copyright © The International Journal of Control, Automation, and Systems.
Chenchen Sun, Guofang Gong*, and Huayong Yang
Zhejiang University
In this paper, a novel adaptive fuzzy immune feedback reaching law (AFIFRL) based sliding mode control (SMC) strategy is proposed for uncertain nonlinear systems with time-varying disturbances. First, a nonlinear immune feedback reaching law (IFRL) inspired by biological immune feedback regulation mechanism is designed to alleviate chattering effect without losing the robustness against disturbances. Second, an improved IFRL is developed in a thin boundary layer to enhance tracking performance. Then, the applied fuzzy controller adjusts the boundary layer online to further improve control performance despite large system uncertainties and disturbances. Furthermore, an adaptive law is employed to estimate the unknown bound of uncertainties, which can effectively attenuate chattering and minimize control effort. The stability analysis is derived by Lyapunov stability theorem. Finally, numerical simulations are conducted to evidence the effectiveness and superiority of the proposed AFIFRL based SMC scheme.
Keywords: Adaptive control, biological immune mechanisms, chattering elimination, fuzzy logic, immune feedback reaching law, sliding mode control.
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