基于模糊神经网络的机械手轨迹跟踪控制系统  

Trajectory Tracking Control System of Manipulator Based on Fuzzy Neural Network

作　　者：缸明义[1] 夏兴国[1] 张庆丰[1] 吴彩林[1] GANG Mingyi;XIA Xingguo;ZHANG Qingfeng;WU Cailin(Department of Electrical Engineering,Ma´anshan Technical College,Ma´anshan 243031,Anhui,China)

机构地区：[1]马鞍山职业技术学院电气工程系,安徽马鞍山243031

出　　处：《江汉大学学报（自然科学版）》2021年第1期66-73,共8页Journal of Jianghan University：Natural Science Edition

基　　金：安徽省高校自然科学研究重点项目(KJ2019A1245,KJ2017A893);安徽省高校优秀青年人才支持计划重点项目(gxyqZD2018105);2017年度安徽省高校学科(专业)拔尖人才学术资助项目(gxbjZD59)。

摘　　要：机械手系统是一个具备高度耦合、非线性等动力学特性且系统结构和参数在实际工作中存在诸多不可预知因素的多输入多输出系统。针对该系统设计了一种模糊神经网络的控制器,并结合粒子群算法和BP算法对FNNC的参数进行优化。通过试验仿真分析,验证了该方案对控制系统有较强的适应性、稳定性以及抗干扰性能,有效地解决了机械手的轨迹跟踪问题。The manipulator system is a multi-input and multi-output system with highly coupled,nonlinear dynamic characteristics and many unpredictable factors in its structure and parameters in practical work.A fuzzy neural network controller is designed for this system,and the parameters of FNNC are optimized by combining particle swarm optimization algorithm and BP algorithm.The simulation results show that the scheme has strong adaptability,stability,and anti-interference performance to the control system,and effectively solves the trajectory tracking problem of the manipulator.

关 键 词：机械手 模糊神经网络 粒子群优化算法 

分 类 号：TP241[自动化与计算机技术—检测技术与自动化装置]