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In response to the limitations of modern industrial processes in terms of control accuracy and safety, this paper proposes a robust predictive fault-tolerant control method based on signal compensation. This method is generally applicable to nonlinear industrial processes with uncertainty and partial actuator failures. Firstly, a novel model is established for nonlinear industrial processes which includes fault factors and unknown lumped dynamic nonlinear terms. On this basis, sub-compensators are designed to eliminate the influence of unmodeled dynamics on the control effect. This method effectively reduces the conservatism of traditional fault-tolerant control and improves the tracking performance of the control system. In addition, this article provides a detailed demonstration of the stability and convergence of the closed-loop system, and verifies the effectiveness of the proposed method through comparative experiments. The experimental results demonstrate that the proposed method exhibits a excellent control performance in comparison to several mainstream methods.
Shi et al. (Thu,) studied this question.