| 粒子群神经网络辨识的机器人分数阶滑模控制 |
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| 引用本文： | 吴方圆,姚江云.粒子群神经网络辨识的机器人分数阶滑模控制[J].电子测量技术,2019,42(9):10-13. |
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| 作者姓名： | 吴方圆 姚江云 |
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| 作者单位： | 广西曙光知识产权服务有限公司 南宁530000;广西科技大学鹿山学院 柳州545616 |
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| 基金项目： | 广西科技基地和人才专项(AD16380042)、2017年度广西高校中青年教师基础能力提升项目（2017KY1389）资助 |
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| 摘 要： | 研究了一种粒子群算法优化的神经网络分数阶滑模变结构控制方法,并将其应用到工业机器人路径跟踪研究中。首先采用粒子群算法优化的神经网络辨识工业机器人的系统模型,训练得到与系统控制参数解析度最相关的模型;然后基于分数阶理论与滑模变结构理论设计了分数阶滑模变结构控制器,作为系统的主控制器应用到工业机器人轨迹跟踪控制系统中。仿真及实验结果表明,该方法具有良好的跟踪性能和快速性。
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| 关 键 词： | 粒子群 神经网络 分数阶滑模控制 工业机器人 |
Fractional order sliding mode control of industrial robot based on particle swarm optimization neural network |
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| Wu Fangyuan,Yao Jiangyun.Fractional order sliding mode control of industrial robot based on particle swarm optimization neural network[J].Electronic Measurement Technology,2019,42(9):10-13. |
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| Authors: | Wu Fangyuan Yao Jiangyun |
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| Affiliation: | (Guangxi Aurora Intellectual Property Service Co. Ltd,Nanning 530000,China;Lushan College of Guangxi University of Science and Technology,Liuzhou 545616,China) |
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| Abstract: | A method of fractional sliding mode variable structure control method based on neural network optimized by particle swarm optimization (PSO) is studied and applied to the path tracking of industrial robots. Firstly, the neural network optimized by particle swarm optimization is used to identify the system model of industrial robots, and the model most relevant to the resolution of system control parameters is trained. Then, the fractional order sliding mode variable structure controller is designed based on fractional order theory and sliding mode variable structure theory, which is applied to the path tracking of industrial robots as the main controller.Simulation and experimental results show that this method has good tracking performance, fast and robust. |
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| Keywords: | particle swarm neural network fractional order sliding mode control industrial robot |
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