基于介电弹性体驱动器的软体机器人建模与跟踪控制
Modeling and tracking control for soft robots of dielectric elastomer actuators
摘要点击 49  全文点击 42  投稿时间:2018-12-10  修订日期:2019-07-06
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DOI编号  10.7641/CTA.2019.80965
  2020,37(4):871-880
中文关键词  介电弹性体驱动器  Gent模型  径向基网络  状态观测器  滑模控制
英文关键词  Dielectric elastomer actuator  Gent model  Radial basis function networks  State observer  Sliding mode control
基金项目  国家自然科学基金
学科分类代码  
作者单位E-mail
王亚午 中国地质大学(武汉)自动化学院 wangyawu@cug.edu.cn 
叶雯珺 康考迪亚大学  
张一龙 东北电力大学  
赖旭芝 中国地质大学(武汉)  
吴敏 中国地质大学(武汉)  
苏春翌 康考迪亚大学工程与计算机科学学院 cysu@alcor.concordia.ca 
中文摘要
      针对基于介电弹性体驱动器的软体机器人的跟踪控制问题, 本文提出一种自适应鲁棒控制策略. 根据虚功原理建立介电弹性体驱动器的动力学模型, 模型中弹性势能部分采用Gent模型进行描述. 考虑到介电弹性体驱动器的精确模型参数难以获取, 使用基于径向基神经网络的逼近器对模型中的未知项进行估计. 同时, 考虑到介电弹性体驱动器形变量的变化率难以被测量, 设计状态观测器对系统未知状态量进行观测. 根据逼近器的估计结果和状态观测器的观测结果, 设计滑模控制器实现介电弹性体驱动器的跟踪控制目标. 最后, 通过数值仿真实验验证所提控制策略的有效性.
英文摘要
      This paper proposes an adaptive robust control strategy for dielectric elastomer actuators (DEAs) utilized in soft robots to achieve their tracking control. The dynamic model of the DEA is developed based on the principle of virtual work, whose elastic energy is described by the Gent model. Since the model parameters of the DEA are difficult to obtain, two approximators based on the radial basis function neural networks (RBFNNs) are employed to estimate the unknown items of the dynamic model. Meanwhile, due to the fact that the rate of the stretch of the DEA is difficult to measure, the state observer is designed to estimate the system states. Based on the approximation results and the observed states, the sliding mode controller (SMC) is designed to realize the trajectory tracking control of the DEA. Finally, the simulation results demonstrate the effectiveness of the proposed control strategy.