基于改进双模糊PID控制的Stewart平台运动路径跟踪研究  被引量:4

Research on Motion Path Tracking of Stewart Platform Based on Improved Double Fuzzy PID Control

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作  者:张娅[1] ZHANG Ya(The College of Intelligent Manufacturing and Automotive,Chongqing Technology and Business Institute,Chongqing 401520,China)

机构地区:[1]重庆工商职业学院智能制造与汽车学院,重庆401520

出  处:《机床与液压》2020年第17期39-43,共5页Machine Tool & Hydraulics

基  金:重庆市重点产业共性关键技术创新专项资助项目(cstc2015zdcy-ztzx0190)。

摘  要:为提高Stewart平台运动控制的抗干扰能力,设计了改进双模糊PID控制系统,并对控制误差进行仿真验证。在坐标系中创建Stewart平台简图,通过矩阵变换推导出连杆运动方程式。设计了Stewart平台液压驱动机构,给出了液压伺服阀流量控制方程式。在传统PID控制基础上设计了双模糊PID控制器,通过粒子群算法对双模糊PID控制器进行优化,采用MATLAB软件对Stewart平台运动路径跟踪误差进行仿真。仿真结果表明:采用改进双模糊PID控制器,Stewart平台在有干扰环境中移动时,仍然能够保持较高的运动路径跟踪精度,对外界的干扰反应速度较快、调节效果较好。采用改进双模糊PID控制器,Stewart平台控制系统的抗干扰能力较强,提高了Stewart平台运动路径跟踪精度。In order to improve the anti-interference ability of motion control of a Stewart platform,an improved double fuzzy PID control system was designed,and the control error was verified by simulation.The Stewart platform sketch was created in the coordinate system,and the motion equation of the connecting rod was deduced by using matrix transformation.The hydraulic drive mechanism of Stewart platform was designed,and the flow control equation of hydraulic servo valve was given.Based on the traditional PID control,a double fuzzy PID controller was designed,and the double fuzzy PID controller was optimized by using particle swarm optimization.The motion path tracking error of Stewart platform was simulated using MATLAB software.The simulation result shows that by using the improved double fuzzy PID controller,the Stewart platform motion path can still maintain a high tracking accuracy when moving in the interference environment,and the response speed is fast and the adjustment effect is good to the external interference.By using the improved double fuzzy PID controller,the anti-interference ability of the Stewart platform control system is strong,and the tracking accuracy of the Stewart platform motion path is improved.

关 键 词:STEWART平台 双模糊PID控制器 粒子群算法 液压驱动机构 运动路径 

分 类 号:TP242[自动化与计算机技术—检测技术与自动化装置]

 

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