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- 저자 : Maiying Zhong (검색결과 2 건)
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An Observer and Post Filter Based Scheme for Fault Estimation of Nonlinear Systems
Hai Liu,Maiying Zhong,Yang Liu,Zuqiang Yang 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.8
The problem of actuator fault estimation for a kind of nonlinear discrete time varying (NDTV) systems is investigated. Norm bounded disturbance is considered and the nonlinear function is assumed to fulfill a Lipschitzlike condition. Fault estimation is accomplished by a novel nonlinear state observer and a dynamic post filter. First, the nonlinear state observer is designed with the help of the small gain theorem and the H∞ filtering approach. Then for the error dynamic of the observer, the dynamic post filter is constructed to estimate the fault. In this scheme, no approximation of the nonlinear function is taken, and the problem of infeasibility resulting from multiple synthesis conditions is considerably improved. Simulation studies are carried out with a nonlinear unmanned aerial vehicle (UAV) model. The turbulent condition is considered and the feed back control loop is employed. Simulation results show that the proposed method can accomplish the estimation work, while the residual evaluation based approach fails to detect the fault.
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Jiao Qin,Maiying Zhong,Wendong Gai,Zhongjun Ding 제어·로봇·시스템학회 2024 International Journal of Control, Automation, and Vol.22 No.4
Due to the complexity of the underwater vehicle itself and its operating environment, it is difficult for fault detection and diagnosis (FDD) unit to obtain accurate fault information in time, which brings difficulties to the implementation of subsequent fault-tolerant control (FTC). Aiming at this question, a novel FTC method is proposed in this paper, which does not rely on FDD units and does not require any prior knowledge of faults. Firstly, a nonlinear continuous time system will be established to describe the underwater vehicle system dynamics with external disturbance, model uncertainties, propeller saturation and unknown propeller faults. To be specific, the nominal controller and fault-tolerant controller are designed respectively. When there is no fault, a nominal controller is used to realize the trajectory tracking control of the underwater vehicle and a quadratic performance index is used to describe and monitor the system performance. Based on the approximation ability of neural networks, a deep deterministic policy gradient (DDPG) algorithm is used to generate the controller compensation signal when the tracking performance degradation caused by propeller fault exceeds the pre-set threshold, so as to realize FTC. Finally, the effectiveness and feasibility of our proposed scheme are verified by simulation.
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