Fuzzy Gain Scheduled Fractional-Order PID Temperature Control of a Continuous Stirred Tank Reactor Process

Abstract

CSTR is one of the most common reactors used for chemical production in all chemical industries, in which reactants continuously enter to the reactor while products are continuously leave from the reactor. CSTR is a highly nonlinear process exhibiting stable and unstable equilibrium points. In this regard, designing a single controller for stable and unstable regions is impossible. In this research work, fuzzy gain scheduling fractional-orderPID (FOPID) temperature control of a CSTR process has been investigated. The mathematical modeling of the CSTR process based on mass and energy balance inside the reactor is done. Due to its nonlinearity and instability, the entire region divides into two regions. Two local FOPID controllers are designed for each region. The parameters of the FOPID controllers are tuned by a genetic algorithm (GA). In order to minimize the overshoot of the control signal the tuning of the controllers is done based on the integral absolute error and control input (IAEU). Then, a fuzzy gain scheduling method is used to smoothly select a local controller suitable for the current operating region. This is done based on the schedular variable (reactor temperature) and then it combined by the Tagaki Sugno fuzzy model. The entire system including the controller design is implemented in MATLAB/Simulink. Also, the performance of the controller has been evaluated based on the setpoint tracking and disturbance rejection capabilities. The performance of the controller tuning is measured using an integral absolute error (IAE). A comparative analysis with two existing works (PID controller and adaptive nonlinear controller) is investigated. From the simulation result the proposed controller gives a settling time of 1.0232, overshoot 0%, in a 0.886 for setpoint tracking response. For the disturbance rejection, the proposed controller gives a settling time of 7.3426, overshoot 7.1%, and IAE of 0.0021 in a 0.886 setpoint tracking response, The simulation results have shown that, the proposed fuzzy gain scheduled FOPID controller outperformed the existing control systems