基于改进型蚁狮算法的PID控制器参数优化

由于被控对象往往具有高阶非线性等特点，传统PID( Proportion Integration Differentiation) 控制器参数整定方法容易使控制器出现超调、震荡、性能变差等缺陷。为此，提出运用将蚂蚁和蚁狮的移动步长进行改进的蚁狮算法对参数进行优化，通过其互动关系，选择最佳蚁狮位置确定控制器参数，并与改进前蚁狮算法及其他优化算法进行了对比。仿真结果表明，基于改进型蚁狮算法的PID 控制器具有较好的性能指标，相比于改进前蚁狮算法、遗传算法和粒子群算法，该算法具有较高的系统控制精度，以及较短的响应时间等优点，且算法实现更加简单，证明了该方法对于优化PID 参数具有优越性和有效性，为PID 控制器的参数优化提供了参考。

Parameter Optimization of PID Controller Based on Improved Ant Lion Optimization Algorithm#br#

Because of the high order nonlinearity of the controlled object，the traditional PID ( Proportion Integration Differentiation) controller of parameter tuning method can easily lead to overshoot，oscillation and poor performance for the controller． To solve this problem，the parameters are optimized by using the ant lion algorithm which improves the moving step size of ants and ant lions． The optimal position of ant lion is selected to determine the controller parameters through its interaction relationship，and the algorithm is compared with the former ant lion algorithm and other optimization algorithms． The simulation results show that the PID controller based on the improved ant lion algorithm has better performance index． Compared with the former ant lion algorithm，genetic algorithm and particle swarm optimization，this algorithm has the advantages of higher system control accuracy and shorter response time，and its implementation is simpler． This method has superiority and validity in optimizing the parameters of PID controller，and provides a reference for the parameter optimization of PID controller．