摘要
研究自动控制系统优化问题,控制系统响应特性取决于系统参数的调整。针对传统的PID控制算法参数较多,且难以整定,使得控制效果不理想等问题,提出了自适应遗传算法的PID参数整定。根据遗传算法具有在线性差的问题,对遗传算法作了改进。通过自适应遗传算法对PID参数进行整定与寻优,选择自适应度大的个体所对应的PID控制参数作为采样时间下的PID控制参数。改进后的算法有效提高了遗传算法的寻优能力,提高了算法的收敛的速度,在一定的范围可以求得最优全局解。在MATLAB上仿真结果表明,在PID参数的寻优过程中,自适应遗传算法具有更强的寻优能力,提高了控制系统的自适应性,为优化控制系统设计提供了依据。
For the many parameters and difficult setting,the traditional PID control algorithm can notthe implement effective control.An adaptive genetic algorithm was proposed based on the PID parameter tuning algorithm.The genetic algorithm with poor linear was improved.The adaptive genetic algorithm was used in tuning of PID parameters and optimization,and the the individual PID control parameters with high fitness value was selected as the PID control parameters at the sampling time.The improved algorithm can effectively improve the optimization ability of genetic algorithms and the convergence speed.The global optimal solution can be obtained in a certain range.The simulation results based on MATLAB show that in the optimization process of the PID parameters,the adaptive genetic algorithm has stronger ability to enhance the adaptability of the control system.
出处
《计算机仿真》
CSCD
北大核心
2011年第12期154-157,共4页
Computer Simulation
关键词
遗传算法
参数
自适应
Genetic algorithms（GA）
Parameter
Adaptive
