A Study Of The Algorithms Of Fuzzy PID Control Based Intelligent Optimization

In this paper, fuzzy PID controller based on T-S model has been studied. Due to lacks of criterion of optimization and excessive tuning parameters, the adaptive genetic algorithm with variable cross and mutation probability is used to optimize the parameters and the performance of control systems is improved. Firstly, based on modified PID-FLC with four fuzzy rules, scaling factor and the fuzzy consequent parameters are optimized by AGA with multiple performance indexes respectively. Many examples show that the dynamic and static performance can be improved apparently by optimization. Secondly, based on T-S model and parameters tuning method of PID controller, fuzzy rules are established and the AGA is used to tune and optimize the parameters. The results of simulation for the main steam temperature of a supercritical once-through 600MW boiler steam generator show good control properties and performances of disturbance attenuation.Yu Qinbo(control theory and engineering) Directed by prof. Jin Weigang...