online updating of uncertain chemical reactor model for design of reliable model-based controller with input saturation

Handling time-varying uncertainties in chemical reactor dynamics poses a significant challenge when designing reliable model-based controllers. this study introduces a novel optimization-based approach to update a nominal dynamic model, initially selected for a continuous stirred tank reactor (cstr). in this approach, a complementary term is calculated online using the system output. this term is then appended to the state space model of the system to compensate for time-varying uncertainties. after confirming the accuracy and reliability of the constructed model, it is used to design a reliable model-based controller for the nonlinear cstr. the efficiency of the designed adaptive controller, which upgrades itself to actual conditions, is compared with a sliding mode controller in the presence of perturbations. additionally, the saturation of the control input is modeled using the framework of a constrained optimization problem solved by karush-kuhn-tucker (kkt) theorem. the constrained stability of the controller is analyzed by the lyapunov method. comparative simulation results show the superior performance of the proposed controller by accurate estimation of time-varying uncertainties under saturated control input.