力矩输入有界的柔性关节机器人轨迹跟踪控制  

Trajectory tracking control for flexible-joint robot manipulators with bounded torque inputs

作　　者：刘华山[1] 金元林 程新[1] 王泽宇 齐洁[1] 刘洋 LIU Hua-shan;JIN Yuan-lin;CHENG Xin;WANG Ze-yu;QI Jie;LIU Yang(College of Information Science and Technology,Donghua University,Shanghai 201620,China;College of Mechanical Engineering,Donghua University,Shanghai 201620,China)

机构地区：[1]东华大学信息科学与技术学院,上海201620 [2]东华大学机械工程学院,上海201620

出　　处：《控制理论与应用》2019年第6期983-992,共10页Control Theory & Applications

基　　金：国家自然科学基金项目(61203337,61773112);上海市自然科学基金项目(17ZR1400100,16ZR140120);上海市青年科技启明星计划项目(19QA1400400);上海市晨光计划项目(13CG29);上海市青年科技英才杨帆计划项目(18YF1400900)资助~~

摘　　要：为解决柔性关节机器人在关节驱动力矩输出受限情况下的轨迹跟踪控制问题,提出一种基于奇异摄动理论的有界控制器.首先,利用奇异摄动理论将柔性关节机器人动力学模型解耦成快、慢两个子系统.然后,引入一类平滑饱和函数和径向基函数神经网络非线性逼近手段,依据反步策略设计了针对慢子系统的有界控制器.在快子系统的有界控制器设计中,通过关节弹性力矩跟踪误差的滤波处理加速系统的收敛.同时,在快、慢子系统控制器中均采用模糊逻辑实现控制参数的在线动态自调整.此外,结合李雅普诺夫稳定理论给出了严格的系统稳定性证明.最后,通过仿真对比实验验证了所提出控制方法的有效性和优越性.In order to solve the problem of trajectory tracking control for flexible-joint robot manipulators with limited output torque,a bounded controller based on singular perturbation theory is proposed.Firstly,the dynamics model of the flexible-joint robot manipulator is transformed into a fast subsystem and a slow subsystem by singularly perturbed decoupling method.Then,invoking a class of smooth saturation function and radial basis function neural network for nonlinear approximation,a bounded controller for the slow subsystem is designed by the back-stepping method.On the other side,in the bounded controller design for the fast subsystem,the convergence of the system is accelerated by filtering the tracking error of the joint elastic torque.At the same time,the fuzzy logic is used in the controllers for the fast and slow subsystems to realize the online dynamic self-tuning of control gains.In addition,the strict stability of system is proved with the Lyapunov stability theory.Finally,simulation results verify the effectiveness and superiority of the proposed approach.

关 键 词：机器人 柔性关节 轨迹跟踪 有界控制 奇异摄动 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]