Probability-Based Robust Stochastic Predictive Fault-Tolerant Control for Industrial Processes With Actuator Failures and Interval Time-Varying Delays

A stochastic robust predictive fault-tolerant control (SRPFTC) method is proposed for industrial processes with interval time-varying delays and actuator failures occurring under a certain probability. Its main contribution is to propose a new control strategy for time-delay systems where actuator failures meet a certain probability, which improve the traditional fault-tolerant control (FTC) method. First of all, an extended state space model composing of the state and output error is established to describe a type of industrial processes with interval time-varying delays, uncertainties, unknown disturbances and actuator failures occurring under a certain probability. Secondly, based on stochastic Lyapunov function theory, robust model predictive control method, time delay upper and lower bounds and linear matrix inequality theory, the stochastic stability conditions of the above the equivalent model are given. Then the control law updated in real time according to the probability of actuator failure is also given. This not only ensures the tracking control under different conditions (normal or fault), but also reduces the energy consumption of traditional FTC methods. Lastly, the effectiveness and feasibility are verified by the case study of the TTS20 water tank.