改进麻雀搜索算法的四旋翼PID参数优化设计  

PID Parameter Optimization Design of Quadrotor UAV Based on Improved Sparrow Search Algorithm

作　　者：徐伟业 钟小勇[1] XU Wei-ye;ZHONG Xiao-yong(School of Science,Jiangxi University of Science and Technology,Ganzhou Jiangxi 341000,China)

机构地区：[1]江西理工大学理学院,江西赣州341000

出　　处：《计算机仿真》2024年第1期48-52,320,共6页Computer Simulation

基　　金：国家自然科学基金项目(51665019);江西省研究生创新专项资金项目(YC2021-S601)。

摘　　要：针对四旋翼无人机PID控制器参数人工整定复杂、费时且难以确保最优的问题,提出一种基于改进麻雀搜索算法的PID参数优化方法,用于四旋翼无人机控制系统。首先引入Piecewise混沌映射,增强初始种群分布的均匀性;其次在探索者位置更新公式中加入动态惯性权重,提升算法全局优化性能;最后结合自适应混合变异策略和历史最优值,增强变异的多样性、提高算法的搜索效率及精度。仿真结果表明,相比于标准麻雀搜索算法、粒子群算法和遗传算法,用改进麻雀搜索算法优化串级PID控制器参数,能够使控制系统具有更快的响应速度、更高的稳态精度。A PID parameter optimization method based on the improved sparrow search algorithm is proposed for the control system of quadcopter drones,which is complex,time-consuming,and difficult to ensure optimal manual tuning of PID controller parameters.Firstly,Piecewise chaos map was introduced for enhancing the uniformity of the initial population distribution;Secondly,dynamic inertia weight was added into the explorer position update formula,so as to promote the global optimization performance of the algorithm;Finally,the adaptive hybrid variation strategy and historical optimal value were combined to strengthen the diversity of variation,and to improve the search efficiency and accuracy of the algorithm.The simulation results show that compared to the standard sparrow search algorithm,particle swarm optimization algorithm,and genetic algorithm,optimizing the parameters of the cascade PID controller using the improved sparrow search algorithm can make the control system have faster response speed and higher steady-stateaccuracy.

关 键 词：四旋翼无人机 比例-积分-微分控制器 麻雀搜索算法 参数优化 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]