Design of fuzzy iterative learning fault‐tolerant control for batch processes with time‐varying delays

In this paper, a new two‐dimensional (2D) fuzzy composite iterative learning fault‐tolerant control strategy using a 2D Takagi‐Sugeno fuzzy model is proposed for batch processes with time delay and actuator faults. Firstly, based on the local‐sector nonlinearity method, a 2D Takagi‐Sugeno fuzzy model representing the nonlinear batch process with actuator faults is constructed with a series of linear models and nonlinear membership functions. Then, a 2D fuzzy feedback control–based iterative learning fault‐tolerant control strategy is proposed under the constructed model. Using the 2D Lyapunov stability theory, sufficient conditions for system asymptotic stability are given. The fault‐tolerant control law is then designed, guaranteeing system asymptotic stability along time and batches even if the system fails. Finally, the traditional control algorithm, the pure iterative learning control algorithm, and the feedback control–based iterative learning control algorithm proposed in this paper are compared on the level control of the three‐tank system, which proves the effectiveness of the proposed method.

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