A Method of PID Controller Parameter Optimization Based on AB Immune Network Model

In some uncertain systems, parameters of PID controller are still difficult to tune. The main reason is that it is difficult to solve conflicts between static state performance and dynamic performance, track and restrain disturb, robustness and control performance. To overcome those demerits, a PID parameter optimization algorithm, which used the idea of immune genetic algorithm, was proposed in this paper. This new algorithm used an AB immune network model to simulate interaction between antibodies and to calculate concentration of antibody, and it was able to converge to the optimum parameters fast and efficiently according to the given controlled system. The simulation results show the improvement in convergent speed, global stability and robustness of the PID controller efficiently