Research of turbine regulating system based on neuron PID optimal control

Aiming at the nonlinear characteristics of dead-time and saturation in the turbine regulating system, an optimal tuning method of neuron PID controller is presented in this paper for solving the problem to be difficult to tune PID parameters in nonlinear system. The approach uses PID control model as input-output model of neuron, and uses the PID parameters as the weights of neuron. The real-time optimal parameters are achieved through the online training of neuron. Hence, the nonlinear system can be optimally controlled. The research results show that the approach presented has very high control precision and very good online tracking performance in controlling nonlinear systems. so, it is of an effective approach of intelligent control.