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所属单位：自动化学院

发表刊物：Syst. Sci. Control Eng.

摘要：A new neural adaptive compensation control approach for a class of multi-input multi-output (MIMO) uncertain nonlinear systems with actuator failures is proposed in this paper. In order to enlarge the set of compensable actuator failures, an actuator grouping scheme based on multiple model switching and tuning (MMST) is proposed for the nonlinear MIMO minimum phase systems with multiple actuator failures, and RBF neural networks are used to approximate the error of plant model. Then an adaptive compensation scheme based on prescribed performance bound (PPB) which characterizes the convergence rate and maximum overshoot of the tracking error is designed for the system to ensure closed-loop signal boundedness and asymptotic output tracking despite unknown actuator failures. Simulation results are given to show the effectiveness of the control design. © 2018 The Author(s).

是否译文：否

发表时间：2018-01-01

合写作者：Qiu, Xiang-wei

通讯作者：张绍杰