基于迭代学习控制的鳗鱼机器人切向速度跟踪控制

doi:10.13973/j.cnki.robot.170590

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张安翻, 马书根, 李斌, 王明辉, 常健. 基于迭代学习控制的鳗鱼机器人切向速度跟踪控制[J]. 机器人, 2018, 40(6): 769-778.DOI: 10.13973/j.cnki.robot.170590. ZHANG Anfan, MA Shugen, LI Bin, WANG Minghui, CHANG Jian. Tracking Control of Tangential Velocity of Eel Robot Based on Iterative Learning Control. ROBOT, 2018, 40(6): 769-778. DOI: 10.13973/j.cnki.robot.170590.

摘要鳗鱼机器人的动力学模型非线性强、高度欠驱动，导致多关节鳗鱼机器人的切向速度跟踪控制极具挑战．本文采用P型迭代学习控制与步态生成器相结合的方法对多关节鳗鱼机器人的切向速度进行跟踪控制．首先，采用解析牛顿-欧拉法建立非惯性系下的鳗鱼机器人动力学模型，直接获得切向速度子动力学模型；然后，利用带饱和函数的P型迭代学习控制器控制步态参数，并且利用复合能量函数和切向速度子动力学模型分析该控制器的收敛性，得到切向速度跟踪误差的收敛条件；最后，提出鳗鱼机器人的运动控制框架，并对多模块的鳗鱼机器人进行仿真和实验．实验结果表明，实际的切向速度随着迭代次数的增加而逐渐跟踪上了期望的切向速度，故而验证了鳗鱼机器人切向速度跟踪控制器的有效性．

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	马书根
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关键词 ：鳗鱼机器人, 牛顿-欧拉建模, 非惯性系, 迭代学习控制, 切向速度控制

Abstract：Due to the strong nonlinear and high under-actuated of the dynamic model of the eel robot, the tracking control of tangential velocity of the multi-joint eel robot is very challenging. So, the P-type iterative learning control and the gait generator are combined to achieve the tracking control of tangential velocity of the multi-joint eel robot. Firstly, the dynamic model of the eel robot in non-inertial frame is established by using analytical Newton-Euler method, which can obtain the tangential velocity sub-dynamics model directly. Then, the convergence condition of tangential velocity tracking errors is obtained by adopting the P-type iterative learning controller with the saturated function to control the gait parameters, and using the composite energy function and the tangential velocity sub-dynamics model to analyze the convergence of the controller. Finally, the motion control framework of the eel robot is introduced and the multi-module eel robot is simulated and tested. The experiment results demonstrate that the actual tangential velocity can follow the desired tangential velocity as the iteration number increases, which verifies the effectiveness of the tracking controller of tangential velocity of the eel robot.

Key words： eel robot Newton-Euler modeling non-inertial frame iterative learning control tangential velocity control

收稿日期: 2017-10-25 录用日期: 2018-03-07

TP24

基金资助:国家重点研发计划（2017YFB1300101）

通讯作者: 张安翻,zhanganfan@sia.cn E-mail: zhanganfan@sia.cn

作者简介: 张安翻(1989-),女,博士生.研究领域:仿生机器人建模与控制方法
马书根(1963-),男,博士,研究员.研究领域:仿生机器人,防灾救援机器人,环境适应机构学
李斌(1963-),男,硕士,研究员.研究领域:仿生机器人,移动机器人,机器人控制.

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https://robot.sia.cn/CN/10.13973/j.cnki.robot.170590 或 https://robot.sia.cn/CN/Y2018/V40/I6/769

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