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Resilient predictive control for a class of uncertain time-delay systems
作者单位:Zhang Qunliang(Dept. of Automation, Shanghai Jiaotong Univ., Shanghai 200240, P.R. China) ; Xi Yugeng(Dept. of Automation, Shanghai Jiaotong Univ., Shanghai 200240, P.R. China) ;
摘    要:In practice, gain perturbations of controllers which are caused by actuator degradation and other reasons often lead to performance degradation. They are capable of violating the closed-loop stability. For a system with constrained inputs, the actual controllers might exceed their limits because of gain perturbations. By the reason, this article considers the problem of resilient predictive control for a class of uncertain time-delay systems. By describing the gain perturbation as a time-varying uncertainty, the sufficient conditions to ensure the closedloop stability and the input constraints are derived. Additionally, an approach to design the resilient predictive controllers is presented in terms of LMI. Finally, the simulation shows that the proposed approach is very effective.

收稿时间:29 November 2005

Resilient predictive control for a class of uncertain time-delay systems
Authors:Zhang Qunliang  Xi Yugeng
Institution:Dept. of Automation, Shanghai Jiaotong Univ., Shanghai 200240, P.R. China
Abstract:In practice, gain perturbations of controllers which are caused by actuator degradation and other reasons often lead to performance degradation. They are capable of violating the closed-loop stability. For a system with constrained inputs, the actual controllers might exceed their limits because of gain perturbations. By the reason, this article considers the problem of resilient predictive control for a class of uncertain time-delay systems. By describing the gain perturbation as a time-varying uncertainty, the sufficient conditions to ensure the closedloop stability and the input constraints are derived. Additionally, an approach to design the resilient predictive controllers is presented in terms of LMI. Finally, the simulation shows that the proposed approach is very effective.
Keywords:Gain perturbations  Constraints  Resilient predictive controllers  Stability
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