Robust asynchronous fuzzy predictive fault-tolerant tracking control for nonlinear multi-phase batch processes with time-varying reference trajectories

For nonlinear multi-phase batch processes with time-varying reference trajectories, actuator faults and nonlinear characteristics, a robust asynchronous fuzzy predictive fault-tolerant tracking control method is proposed. First, considering an asynchronous switching situation between a state and a controller when switching occurs, an extended Takagi-Sugeno fuzzy switching model, including the matched and mismatched cases, is established. Then, a robust asynchronous fuzzy predictive fault-tolerant tracking controller is constructed based on the switching model by taking into account whether the model rules match the controller rules. Second, in order to ensure the stability of the system, the conditions for system stability indicated by the linear matrix inequality are provided using the relevant theories and methodologies. Next, the stability conditions are solved online, which can obtain the gains of control law in each phase, the minimum running time in the matched case, and the maximum running time in the mismatched case. By utilizing the maximum running duration allows the switching signal to be sent out in advance, preventing asynchronous switching situations and ensuring stable system operation. The simulation results finally demonstrate the viability and effectiveness of the developed controller.