Disturbance Observer-based Adaptive Fault-tolerant Dynamic Surface Control of Nonlinear System with Asymmetric Input Saturation
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所属单位：自动化学院
发表刊物：Int. J. Control Autom. Syst.
摘要：In this paper, a composite fault-tolerant control problem is studied for a class of uncertain nonlinear system with asymmetric input constraint, actuator fault and external unmatched disturbance. The radial basis function neural network (RBFNN) is employed to approximate the unknown uncertainty and asymmetric input saturation. The approximation error, external unmatched disturbance and actuator faults are integrated as the compounded disturbance. A nonlinear disturbance observer is designed to tackle the effect of the compounded disturbance which can be separated from the controller design. To handle the effect of asymmetric input saturation, a smooth continuous differentiable saturation model is explored. Adaptive NN fault-tolerant control scheme is developed to guarantee that all the signals in the closed-loop systems are semiglobally uniformly ultimately bounded (SGUUB) and the tracking errors converge to a small neighborhood of origin by choosing the appropriate design parameters. The effectiveness of the proposed control scheme is demonstrated in the simulation study. © 2019, ICROS, KIEE and Springer.
ISSN号：1598-6446
是否译文：否
发表时间：2019-03-01
合写作者：龚华军,刘春生
通讯作者：汪丽影