【摘要】 针对基于简单遗传算法(SGA)进行PID整定在收敛性及初值敏感度方面的缺陷,提出了基于分布式并行遗传算法(PGA)的PID参数整定方法。该方法可以将不同遗传操作的优点加以整合,通过并行运算提高整定效率,能够更有效地进行参数优化。选用典型被控对象仿真,并分别进行收敛性分析与初值敏感度分析。仿真试验表明与SGA相比PGA提高了局部搜索空间的微调能力,降低了对初值的敏感度,寻优效果也大为改善,从而说明了这种方法的可行性,为PID参数整定方法提供了一种新的尝试。更多还原

【Abstract】 Aiming at the deficiency and limitation of simple genetic algorithm(SGA),distributed parallel genetic algorithm(PGA) is proposed to design the parameter optimization of PID controller.in this new algorithm,integrating the optimums of different genetic operator,and using parallel operation to improve the tuning efficiency,it optimizes the parameter more effectively.it analyses astringency and initial value sensitivity with the typical controlled object,applying it into simulator controls,PGA improves the micro adjusting of local search area,reduces the sensitivity of initial value.Then a satisfying performance is obtained,it is showed the feasibility of distributed PG更多还原