改进人工蜂群算法及在自抗扰控制上的应用

Improved Artificial Bee Algorithm and its Application in Active Disturbance Rejection Control

在分析基本人工蜂群算法优缺点的基础上,提出了一种基于混沌全局搜索策略和局部优化搜索策略的改进人工蜂群算法。采用6个标准测试函数,经过仿真测试,验证了该算法与基本蜂群算法相比具有收敛速度快、寻优效果好和寻优效率高的优点。最后针对自抗扰控制器的参数优化难度大、不易寻找的问题,将改进的人工蜂群算法应用到自抗扰控制器的参数优化中,并和串级PID控制系统进行仿真对比。仿真结果表明,改进蜂群算法的自抗扰控制器能以对控制对象进行更快更好的控制,使被控对象处于更好的控制状态下,从而解决了自抗扰控制器参数寻优难度大、不易寻找的问题。

With the analysis of the advantages and disadvantages of the basic artificial bee colony algorithm,an improved artificial bee colony algorithm was proposed based on the chaotic global search strategy and the local optimization search strategy. Using six standard test functions,it was proved that this algorithm has the advantages of fast convergence and good effectiveness in optimization. Finally,this improved artificial bee colony algorithm was applied to the parameter optimization of the auto disturbance rejection controller( ADRC). The simulation results showed that the algorithm can identify more suitable controller parameters at a faster speed,compared to the cascade PID control system.