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所属单位：自动化学院
发表刊物：MATHEMATICAL PROBLEMS IN ENGINEERING
关键字：ADAPTIVE NEURAL-CONTROL TRACKING CONTROL CONTROL SCHEME IDENTIFICATION NETWORKS OBSERVER
摘要：This paper presented a new data-driven robust control scheme for unknown nonlinear systems in the presence of input saturation and external disturbances. According to the input and output data of the nonlinear system, a recurrent neural network (RNN) data-driven model is established to reconstruct the dynamics of the nonlinear system. An adaptive output-feedback controller is developed to approximate the unknown disturbances and a novel input saturation compensation method is used to attenuate the effect of the input saturation. Under the proposed adaptive control scheme, the uniformly ultimately bounded convergence of all the signals of the closed-loop nonlinear system is guaranteed via Lyapunov analysis. The simulation results are given to show the effectiveness of the proposed data-driven robust controller.
ISSN号：1024-123X
是否译文：否
发表时间：2017-01-01
合写作者：王丽,龚华军,刘春生
通讯作者：王莉,王莉