基于免疫粒子群算法的PID参数整定与自适应

PID Parameters Tuning and Adaptation Based on Immunity Particle Swarm Optimization

针对粒子群算法容易陷入早熟以及免疫算法计算过程繁复冗长的缺点,将免疫系统的免疫信息处理机制引入PSO算法中,提出了一种基于免疫选择粒子群的算法(ISPSO)。将ISPSO算法应用到PID控制器的参数整定与自适应中,并设计了相关PID控制器参数。Matlab仿真试验结果表明,该算法能够解决PSO算法早熟收敛的问题,适用于PID控制器的自整定。

To overcome the demerits of particle swarm optimization （ PSO ） and immunity algorithm, i. e. , easily fall into pre-maturity and complicated computing process, the new algorithm named immunity selection PSO （ ISPSO ） is proposed, in this algorithm, the immunity information processing mechanism of immunity system is introduced into PSO. The algorithm is applied into parameters tuning and adaptation of PID controller, to design parameters for PID controller. The Matlab simulation results show that the problem of pre-maturity convergence of PSO algorithm can be solved and the algorithm is suitable for self-tuning of PID controller.