Optimal design of self-tuning fuzzy controller based on immune principle

We designed a global optimization algorithm and a local optimization algorithm based on immune optimization, and then proposed an effective self-tuning scheme of fuzzy controller for time-variable plant. For a time-variable plant, the global optimization algorithm was adopted to optimize nominal controller offline. When the plant changed, new optimal controller could be rapidly obtained by local optimization, then it was switched into control to implement self-tuning control and improve the control performance. Simulations show that the system has strong robustness and can implement high accuracy control for some industrial plants, which strongly support its practical value.