基于改进粒子群算法的机械臂振动抑制研究  

Research on Vibration Suppression of Robotic Arm Based on Improved Particle Swarm Algorithm

作　　者：冯桑[1] 王炳成 张泳 方淦杰 严楷淳 FENG Sang;WANG Bingcheng;ZHANG Yong;FANG Ganjie;YAN Kaichun(School of Electromechanical Engineering,Guangdong University of Technology,Guangzhou Guangdong 510006,China;Institute of Agricultural Economy and Information,Guangdong Academy of Agricultural Sciences,Guangzhou Guangdong 510640,China)

机构地区：[1]广东工业大学机电工程学院,广东广州510006 [2]广东省农业科学院农业经济与信息研究所,广东广州510640

出　　处：《机床与液压》2024年第11期20-26,共7页Machine Tool & Hydraulics

摘　　要：SCARA机械臂在工作过程中和工作终止后都会出现振动问题,为了降低机械臂的残余振动,选取粒子群作为寻最优抑振轨迹的优化算法,针对粒子群算法在轨迹寻优时收敛性差以及出现停滞现象问题,提出采用非线性递减惯性权重和粒子种群跳跃的方法对粒子群算法进行改进。利用机械臂振动抑制实验平台,使用改进的粒子群算法进行抑振轨迹优化并进行实验研究,验证结果可行且有效,得到抑振指标最小的最优抑振轨迹。In order to reduce the residual vibration of SCARA robot arm,particle swarm algorithm was selected as the optimization algorithm to find the optimal vibration suppression trajectory.The method of nonlinear decreasing inertia weight and particle population jumping was proposed to improve the particle swarm algorithm for the problem of poor convergence and stagnation in the trajectory finding of particle swarm algorithm.Using the robotic arm vibration suppression experimental platform,the improved particle swarm algorithm for vibration suppression trajectory optimization is experimentally studied to verify that the results are feasible and effective,and the optimal vibration suppression trajectory with the smallest vibration suppression index is obtained.

关 键 词：SCARA机械臂 改进PSO算法 惯性权重 振动抑制 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]