An adaptive PID control for cement grinding particle size based on simultaneous perturbation stochastic approximation
Considering the problem of the highly dependence on the accuracy model information of the industrial control process, an online PID parameter tuning method is proposed based on the simultaneous perturbation stochastic approximation (SPSA) algorithm and the traditional PID control only by the input and output data of the system. Interfering with each component of the PID controller parameters simultaneously, and the gradient information of the control performance loss function is estimated via the output value after disturbance by the global optimization method of stochastic approximation algorithm. The PID controller parameter is iterative updated according to the gradient estimation value. Finally, we applied this method to the control process of cement grinding particle size, and the simulation results by MATLAB shown it can lead a high control precision which proves the feasibility and effectiveness of this adaptive PID control method.