Abstract: The performance of PID controller depends on the combination of the control parameters. An improved particle swarm optimization was proposed for tuning and optimizing PID parameters, by applying interval algorithm and roulette wheel selection to the initialization of particle location. The simulation and experimental results show that, the proposed algorithm can overcome premature phenomena, reduce the influence of random initial population, and improve the convergence precision, which means a good application prospect.

Key words: PID controller, particle swarm optimization, interval algorithm, roulette wheel selection, premature convergence

摘要： PID控制器的性能取决于其控制参数的组合,针对其参数的整定与优化问题,提出了一种改进的粒子群算法,该算法将区间算法与轮盘赌选择引入种群微粒位置的初始化操作。仿真实验表明,新算法能有效克服早熟收敛现象,降低随机性初始种群的影响,提高算法收敛精度。

关键词: PID控制器, 粒子群算法, 区间算法, 轮盘赌选择, 早熟收敛