改进遗传算法及其在倒立摆控制中应用研究

针对标准遗传算法寻优时存在的个体多样性不足、搜索速度迟缓、容易陷入局优的问题，使用自适应调整的交叉算子和变异算子对其进行改进，并利用改进的遗传算法对直线一级倒立摆模型实现稳定控制的关键参数进行寻优。在Python3.8软件上对寻优过程进行仿真，仿真结果表明，改进的遗传算法可以更好的平衡全局搜索和局部寻优能力，在实验中展现了良好的效果。

Improved Genetic Algorithm and Research on the Control System of Inverted Pendulum

In order to solve the problems of lack of individual diversity, slow search speed and easy to fall into local optimization in the optimization of standard genetic algorithm, the crossover operator and mutation operator of adaptive adjustment are used to improve the algorithm, and the key parameters of stable control of linear one-stage inverted pendulum model are optimized by using the improved genetic algorithm. The optimization process is simulated on Python3.8 software. The simulation results show that the improved genetic algorithm can better balance the global search and local search ability, and shows good results in the experiment.