Analysis of hybrid temperature control for nonlinear continuous stirred tank reactor

Abstract

Classical controllers usually require a prior knowledge of mathematical modeling of the process. The inaccuracy of mathematical modeling degrades the control performance of the continuous stirred tank reactor (CSTR), which shows nonlinearity to some extent. It is very necessary to attain desired temperature within a specified period of time to avoid overshoot and absolute error, with better temperature tracking capability, else the process is disturbed in the nonlinear CSTR system. This paper studies the output (temperature) tracking and disturbance rejection problem of nonlinear CSTR control systems with uncertainties via classical control PID, cascade control, and hybrid intelligent controller that includes FLC, adaptive control, and adaptive neuro-fuzzy inference system (ANFIS). This paper evaluates change in an adaptive controller response with varying adaptive gain. It has been observed that OLTF of CSTR is stable, and adaptive controller is best suitable for temperature control for ISE, and also has much better temperature tracking capability. Adaptive controller and ANFIS both have observed zero overshoot.