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出 处:《浙江大学学报(工学版)》2006年第12期2144-2148,共5页Journal of Zhejiang University:Engineering Science
摘 要:针对耦合和非线性永磁同步电机(PMSM)控制器优化设计的难题,提出了基于粒子群优化(PSO)算法的比例、积分和微分(PID)控制器的优化设计方法.结合PSO的基本原理和PMSM伺服系统的控制策略,给出了优化PID控制器设计的步骤.考虑到综合评价系统的各项性能指标,在优化过程中引入了新的模糊汉明距离的评价策略.同时对遗传算法(GA)和PSO算法优化结果进行对比研究.仿真和实验结果表明,该方法能搜寻到最优或次最优的参数空间,并能取得比GA更好的空间解.优化得到的PID控制器速度响应快、超调量小,有效地提高了伺服系统的动态性能.To deal with the difficulties in optimal controller design for coupled and nonlinear permanent magnet synchronous motor (PMSM) servo system, a novel proportional-integral-derivative (PID) controller design method was proposed based on particle swarm optimization (PSO) algorithm. By combining the principle of PSO and control strategy for the PMSM servo system, the procedures for optimal PID controller design were achieved. Considering overall evaluation of the system performance, a new evaluation strategy using fuzzy hamming distance was introduced during the optimization process. Comparison studies between the optimized data obtained by genetic algorithm (GA) and those by PSO algorithm were made. The simulation and experimental results show that the proposed method can locate the optimal or near optimal parameter space, achieve a better solution space than the GA method. The optimized PID controller has rapid response and low overshoot, and can effectively improve the dynamic performance for the servo system.
关 键 词:粒子群优化 遗传算法 比例 积分微分控制器 永磁同步电机伺服系统
分 类 号:TP271.4[自动化与计算机技术—检测技术与自动化装置]
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