Robust dynamic output feedback predictive fault‐tolerant control for discrete uncertain systems

Shiqi Wang, Hui Li, Hua Li, Huiyuan Shi, Qiubai Sun, Ping Li
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Abstract

A robust predictive fault‐tolerance control method integrating dynamic output feedback is proposed for discrete industrial processes with unmeasurable states, actuator faults, uncertainties, and external disturbances. First, a new iterative error model is developed, which extends the output tracking error to increase the freedom of controller regulation and ensure the tracking performance of the system. Second, a robust dynamic output feedback predictive fault‐tolerant controller is designed based on the preceding model. According to the Lyapunov stability theory, the robust stability criterion of the system is performed in the case of actuator faults, and the stability conditions of the system in the form of linear matrix inequality are given. The real‐time optimal control law gains are obtained by solving the stability conditions online. This method can effectively suppress the effects of actuator faults, uncertainties and external disturbances on the system with unmeasurable states, which can guarantee the tracking performance and stability of the system. The effectiveness of the proposed method is finally verified by using an injection molding process as an example.
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离散不确定系统的鲁棒动态输出反馈预测容错控制
针对具有不可测状态、执行器故障、不确定性和外部干扰的离散工业过程,提出了一种集成动态输出反馈的鲁棒预测容错控制方法。首先,建立了一个新的迭代误差模型,扩展了输出跟踪误差,增加了控制器调节的自由度,确保了系统的跟踪性能。其次,基于前述模型设计了鲁棒动态输出反馈预测容错控制器。根据李雅普诺夫稳定性理论,对执行器故障情况下的系统进行鲁棒稳定性判据,给出了线性矩阵不等式形式的系统稳定性条件。通过在线求解稳定性条件,获得实时最优控制律增益。该方法能有效抑制执行器故障、不确定性和外部扰动对不可测状态系统的影响,从而保证系统的跟踪性能和稳定性。最后以注塑过程为例,验证了所提方法的有效性。
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