摘要
针对6自由度液压驱动并联机器人的精确控制问题,提出一种结合自适应神经模糊推理系统(ANFIS)和比例积分微分(PID)控制的机器人控制方法。首先,利用浮动坐标系描述法(FFRF)来模拟机器人柔性组件,并构建并联机器人的拉格朗日动力学模型。然后,根据模糊推理中的模糊规则来自适应调整PID控制器参数。最后,利用神经自适应学习算法使模糊逻辑能计算隶属度函数参数,从而使模糊推理系统能追踪给定的输入和输出数据。将该控制器与传统PID控制器、模糊PID控制器进行比较,结果表明,ANFIS自整定PID控制器大大减小了末端器位移误差,能很好地控制并联机器人末端机械手的运动。
For the issues that the precise control of a hydraulic driven parallel manipulator with 6 degrees of freedom, this paper proposed a parallel manipulator control method based on adaptive network fuzzy inference system （ANFIS） and PID control. Firstly, it used a floating frame of reference method （FFRF） to simulate the manipulator flexible components, constructing the Lagrange dynamic model of the parallel manipulator. Then, according to the fuzzy rules in fuzzy reasoning, it derived the parameters of PID controller from the adaptive adjustment. Finally, it used the neural adaptive learning algorithm to make fuzzy logic can calculate the membership function parameters, so that the fuzzy inference system can track the given input and output data. Compared with the traditional PID controller and fuzzy PID controller, the results show that this PID controller can greatly reduce the displacement error of the end effectors, and can accurately control the movement of the manipulator end effectors.
作者
梁娟
赵开新
陈伟
Liang Juan Zhao Kaixin Chen Wei(Dept. of Computer Science ＆ Technology, Henan Institute of Technology, Xinxiang Henan 453002, China College of Automation, Wu- hart University of Technology, Wuhan 430070, China)
出处
《计算机应用研究》
CSCD
北大核心
2016年第12期3586-3590,共5页
Application Research of Computers
基金
国家自然科学基金资助项目(61374151)
河南省高校科技创新人才支持计划项目(13HASTIT040)
河南省教育厅科学技术研究重点资助项目(13A520221)
关键词
并联机器人
自适应神经模糊推理系统
PID控制
动力学模型
parallel manipulator
adaptive network fuzzy inference system（ANFIS）
PID control
dynamic modeling
