Research on tuning parameters for a model predictive controller based on CSA in CSTR process

Continuous Stirred Tank Reactor (CSTR) is a typical and high nonlinear process in process industry .It is difficult to control CSTR process. MPC is an advanced control strategy. But it is hard to tune the MPC parameters. A hybrid algorithm is presented to solve this difficulty and this algorithm is based on the immune clonal selection algorithm and sequential quadratic programming. The framework of tuning parameters based on events trigger is introduced in case of uncertain disturbance. Finally, simulation experiments were done with this algorithm in CSTR .Comparison with the results of set point control proved that the proposed method is more effective than other tuning methods and can be used to control CSTR process.