遗传参数自适应调整算法及其在液压动力系统优化控制中的应用

Adaptive Algorithms of Genetic Algorithm Parameters and Its Application to Hydraulic System Control

针对固定参数的遗传算法容易陷入过早收敛,进入局部最优状态等问题,建立了交叉概率及变异概率的模糊逻辑控制器以实现遗传算法策略性参数的自适应调整,从而提高优化算法的收敛速度及获得全局解的能力。运用常规优化方法及改进优化算法对永磁电机驱动的液压系统流量进行优化控制和对比,仿真和实验结果表明:采用遗传参数自适应调整算法优化控制器,可使系统在典型工况下,保持良好的控制性能,并且具有高于常规优化方法的控制精度和鲁棒性。

Fixed parameters of genetic algorithm are easy to fall into premature convergence and local optimum situation. An improved genetic algorithm was proposed herein in order to improve the convergence speed and the ability to global solution. Fuzzy controller was established in order to a- chieve adaptive adjustment of the genetic algorithm parameters （Pc and Pm）. Through the use of conventional optimization methods, simple genetic algorithms and improved optimization algorithms, complete the control of hydraulic flow driven by （PMSM）. The results show that： using fuzzy logic genetic algorithms a hydraulic system achieves good control performance and strong robustness under typical operating conditions.