A single-nerve cell PID control method with optimization algorithm for coordinated system

Aiming at the characteristics such as multivariable, strong coupling, nonlinear and time-varying parameters for the coordinated control system of unit power plant, a single-nerve cell network combined with PID control method was presented. A modified mutative scale chaotic optimization algorithm was proposed for the use of tuning the weight parameters of neural network and PID parameters. The new control strategy not only retains the characteristics of the traditional PID, such as its simple structure and practicable control algorithm, etc, but also fits to control the nonlinear multivariate systems, and avoids a mass of tuning work in the progress of design. Simulation results show that the control strategy has a better decouple and disturbance rejection ability. The control quality of the coordinated system can be greatly increased.