Output Constrained Adaptive Controller Design for Nonlinear Saturation Systems
This paper considers the adaptive neuro-fuzzy control scheme to solve the output tracking problem for a class of strict-feedback nonlinear systems. Both asymmetric output constraints and input saturation are considered. An asymmetric barrier Lyapunov function with time-varying prescribed performance is presented to tackle the output-tracking error constraints. A high-gain observer is employed to relax the requirement of the Lipschitz continuity about the nonlinear dynamics. To avoid the 'explosion of complexity', the dynamic surface control (DSC) technique is employed to filter the virtual control signal of each subsystem. To deal with the actuator saturation, an additional auxiliary dynamical system is designed. It is theoretically investigated that the parameter estimation and output tracking error are semi-global uniformly ultimately bounded. Two simulation examples are conducted to verify the presented adaptive fuzzy controller design.
Y. Yang et al., "Output Constrained Adaptive Controller Design for Nonlinear Saturation Systems," IEEE/CAA Journal of Automatica Sinica, vol. 8, no. 2, pp. 441-454, Institute of Electrical and Electronics Engineers (IEEE), Nov 2020.
The definitive version is available at https://doi.org/10.1109/JAS.2020.1003524
Electrical and Computer Engineering
Center for High Performance Computing Research
Keywords and Phrases
Asymmetric Barrier Lyapunov Function; Input Saturation; Nussbaum Function; Time-Varying Prescribed Performance
International Standard Serial Number (ISSN)
Article - Journal
© 2020 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
24 Nov 2020