基于蚁群算法固定翼无人机PID参数控制方法

Fixed-wing PID Parameters Tuning Based on Ant Colony Optimization

针对传统固定翼无人机PID控制器比例、积分和微分参数调节控制精度低,响应速度慢,难以得到最优线性PID参数组合等问题。本文利用蚁群算法寻优搜索对传统PID控制器进行改进,本文将PID参数寻优过程转化为多约束条件组合优化问题,并通过蚁群算法针对PID参数整定多次迭代来进行搜索最优数值路径来更加快速,精确的优化PID线性组合参数值,提高对固定翼的精确PID参数控制。

As to the low efficiency of traditional PID tuning for Fixed-Wing UAV（unmanned aerial vehicle）, it＇s difficult to find the optimal problem of linear array.Therefore,we use the ACO（Ant Colony Optimization） to improve the traditional PID controller,and transform traditional PID as combination optimization problem, by using the iteration of ant colony to search the optimal path to look for the more speedy and calculate PID array parameters, by the way to reach more precise control.