自适应遗传算法在数控伺服系统控制参数优化中的应用  

Application of control parameters optimization of CNC servo system based on self-adaptive genetic algorithm

作　　者：李军民[1] 李虎[1] 

机构地区：[1]西安科技大学计算机科学与技术学院,陕西西安710054

出　　处：《西北大学学报（自然科学版）》2011年第3期430-434,共5页Journal of Northwest University（Natural Science Edition）

基　　金：陕西省国际科技合作计划基金资助项目(DK07KW01)

摘　　要：目的研究数控伺服系统的PID参数控制中组合优化问题。方法基于标准遗传算法理论,提出了一种使交叉概率和变异概率随适应度值自动改变的自适应遗传算法。结果在保持种群多样性的同时,保证了算法的收敛性,同时也保持了较好的系统稳定性。结论与传统Ziegler-Nichols算法的PID参数整定进行动态响应性能对比分析与仿真试验,表明基于自适应遗传算法的PID参数整定方法具有一定的优越性,能快速平稳地跟随期望输出值,系统响应具有较好的实时性与控制精度。Aim The combinatorial optimization problem in PID parameter control of the CNC servo system is discussed. Methods Based on the standard genetic algorithm, a PID parameter adjustment method is presented, which makes the probabilities of crossover and mutation automatically change along with the fitness values. Results In keeping the population diversity, it can not only ensure the convergence of the algorithm, but also maintain a better stability of system. Conclusion As compared with the traditional Ziegler-Nichols PID parameters setting algorithm of dynamic response analysis and simulation test performance comparison,it is shown that the PID parameter adjustment based on adaptive genetic algorithm has superiority in terms that it can follow expected output value rapidly and steadily and the system response has a better real-time performance and control precision.

关 键 词：自适应遗传算法 PID参数整定 数控伺服系统 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]