摘  要：針對(duì)一般的粒子群優(yōu)化（PSO）學(xué)習(xí)算法中存在的容易陷入局部最優(yōu)和搜索精度不高的缺點(diǎn)，對(duì)改進(jìn)型PSO算法進(jìn)行研究。由于慣性權(quán)重系數(shù)ω對(duì)算法是否會(huì)陷入局部最優(yōu)起到關(guān)鍵的作用，因此，通過(guò)改變慣性權(quán)重ω的選擇，對(duì)慣性權(quán)重系數(shù)采取線性減小的方法，引入改進(jìn)型的PSO算法。采用改進(jìn)的PSO算法對(duì)PID控制器進(jìn)行參數(shù)優(yōu)化并把得到的最優(yōu)參數(shù)應(yīng)用于控制系統(tǒng)中進(jìn)行仿真。仿真實(shí)驗(yàn)結(jié)果表明：改進(jìn)型PSO算法不會(huì)陷入局部最優(yōu)，能得到全局最優(yōu)的PID控制器的參數(shù)，并使得控制系統(tǒng)的性能指標(biāo)達(dá)到最優(yōu)，控制系統(tǒng)具有較好的魯棒性。
關(guān)鍵詞：粒子群優(yōu)化算法；控制器；參數(shù)優(yōu)化；性能指標(biāo)；魯棒性
中圖分類號(hào)：TP273；TP214；N945.13；TM930.12      文獻(xiàn)標(biāo)志碼：A       文章編號(hào)：1674-5124（2013）05-0096-03
Research on PID controller based on improved PSO algorithm
ZHANG Yan-hong
（School of Electronic Information & Electric Engineering，Changzhou Institute of Technology，
Changzhou 213002，China）
Abstract: For the shortcomings of easily falling into local optimum and lower search precision in common particle swarm optimization（PSO） algorithm， an improved PSO algorithm was studied. The inertia weight coefficient ω plays a key role on whether PSO algorithm falling into local optimum or not， so it is linearly reduced by the improved PSO algorithm. The parameters of PID controller are also optimized by the improved PSO algorithm and the optimized parameters are used in the control system. The simulation results show that the improved PSO algorithm does not fall into local optimal and the optimal parameters of the PID controller can be obtained， which makes the performance index of the control system optimal with better robustness.
Key words: PSO； controller； parameter optimization； performance index； robustness