Iterative learning observer-based predefined-time sliding mode control for continuous stirred tank reactor with input and output constraints

To address the challenge of rapid and precise control in the continuous stirred-tank reactor (CSTR), this paper proposes an iterative learning observer-based predefined-time sliding mode control (SMC) for CSTR with external disturbances and input and output constraints. The iterative learning observer is developed to estimate disturbances. The slide mode control can handle the input and output constraints by a novel sliding mode variable. The predefined-time control ensures that the system states can track their reference signals within the specified time. The stability of the closed-loop system is analyzed and demonstrated using Lyapunov stability theory. The effectiveness and feasibility of the proposed control method are validated through MATLAB/Simulink simulations. Compared to the existing controllers, the proposed controller demonstrates superior performance in both trajectory tracking accuracy and response speed, when the CSTR system was subject to external disturbances and input and output constraints. Under the iterative learning observer-based predefined-time SMC, the convergence time of closed-loop system can be independent of the initial state of the system, which can be designed by tuning the controller parameters.