计算机应用研究
計算機應用研究
계산궤응용연구
APPLICATION RESEARCH OF COMPUTERS
2015年
5期
1376-1378,1382
,共4页
PID 控制器%交叉因子%蚁群遗传混合算法%自适应%信息素
PID 控製器%交扠因子%蟻群遺傳混閤算法%自適應%信息素
PID 공제기%교차인자%의군유전혼합산법%자괄응%신식소
PID controller%aberrance gene%ACS-GA algorithm%self-adapted%information element
针对遗传算法易重复迭代、蚁群算法易陷入停滞的缺点，提出基于自适应蚁群遗传混合算法的 PID 参数优化。先用遗传算法获得 PID 参数的初值，再用改进后的蚁群算法自适应调整路径选择概率和信息素更新规则，最终搜索出 PID 参数的最优值。仿真结果表明，对于给定的被控对象，相比于 GA 和 ACS 算法，该算法搜索出的 Kkp、Kki 、Kkd 最优，系统响应时间短，动态性和稳定性佳，说明该方法整定出的 PID 参数值具有最优性。对于其他的控制对象和过程也具有参考价值。
針對遺傳算法易重複迭代、蟻群算法易陷入停滯的缺點，提齣基于自適應蟻群遺傳混閤算法的 PID 參數優化。先用遺傳算法穫得 PID 參數的初值，再用改進後的蟻群算法自適應調整路徑選擇概率和信息素更新規則，最終搜索齣 PID 參數的最優值。倣真結果錶明，對于給定的被控對象，相比于 GA 和 ACS 算法，該算法搜索齣的 Kkp、Kki 、Kkd 最優，繫統響應時間短，動態性和穩定性佳，說明該方法整定齣的 PID 參數值具有最優性。對于其他的控製對象和過程也具有參攷價值。
침대유전산법역중복질대、의군산법역함입정체적결점，제출기우자괄응의군유전혼합산법적 PID 삼수우화。선용유전산법획득 PID 삼수적초치，재용개진후적의군산법자괄응조정로경선택개솔화신식소경신규칙，최종수색출 PID 삼수적최우치。방진결과표명，대우급정적피공대상，상비우 GA 화 ACS 산법，해산법수색출적 Kkp、Kki 、Kkd 최우，계통향응시간단，동태성화은정성가，설명해방법정정출적 PID 삼수치구유최우성。대우기타적공제대상화과정야구유삼고개치。
This paper proposed a method of self-adapted ant colony algorithm and genetic algorithm for the optimization of pa-rameters of PID controller.This method overcame genetic algorithm’s defects of repeated iteration,ant colony algorithm’s de-fects of got stagnation.This algorithm got initialized pheromone applying genetic algorithm to get PID parameters.Then ran an improved ant colony algorithm,adjusted the influence of each ant to the trail information updating and selected probabilities of the paths.Eventually,obtained the optimal value of PID parameters.For a given system,the results of simulation experiments which compare with Z-N,GA and ACS,the response time is greatly reduced.at the same time the system has good performance and stability.It illustrate that the method is more optimality for setting the value of PID .The experiments show that it also can be used for other process widely.
