新型可重构机器人的模糊自适应控制研究
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摘要
针对一类新型可重构机器人的构型自适应控制问题,采用牛顿—欧拉迭代方法自动生成其通用形式的动力学方程。对方程中含摩擦力及外部扰动的模型不确定项,提出一种模糊自适应算法加以逼近,基于李亚普诺夫稳定性理论设计模糊算法权值参数的自适应调节律,保证闭环系统的稳定性。针对系统存在建模误差问题,引入鲁棒项对其整体补偿以提高系统抗干扰能力。最后,将所提算法应用于3个单元模块所组成的可重构机器人中,采用一机器人的两种不同构型进行对比试验,结果显示该方法能快速适应可重构机器人的构型改变,具有良好的跟踪性能,验证了算法的有效性和可行性。
A fuzzy adaptive control strategy is proposed to study the adaptive position tracking control of a novel reconfigurable robot system. The proposed fuzzy adaptive controller can approximate the model uncertainty of systems, referring mainly to the friction and external disturbance in the automatic generated Newton-Euler dynamic equations. The Lyapunov synthesis approach is used to tune the output weight of the fuzzy controller adaptively in order to guarantee the stability of the closed-loop control system. A robust term is adopted to minify the influence of the modeling error and enhance the whole system's robustness. Finally, the proposed adaptive controller is applied to two different configurations of the same reconfigurable robot which is composed of three modules, and the comparison experiment results show that this control method can quickly adapt to the configuration changes and has good tracking performance, which demonstrates the effectiveness and feasibility of the proposed method.
A fuzzy adaptive control strategy is proposed to study the adaptive position tracking control of a novel reconfigurable robot system. The proposed fuzzy adaptive controller can approximate the model uncertainty of systems, referring mainly to the friction and external disturbance in the automatic generated Newton-Euler dynamic equations. The Lyapunov synthesis approach is used to tune the output weight of the fuzzy controller adaptively in order to guarantee the stability of the closed-loop control system. A robust term is adopted to minify the influence of the modeling error and enhance the whole system's robustness. Finally, the proposed adaptive controller is applied to two different configurations of the same reconfigurable robot which is composed of three modules, and the comparison experiment results show that this control method can quickly adapt to the configuration changes and has good tracking performance, which demonstrates the effectiveness and feasibility of the proposed method.
引文
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[3]曹燕军,葛为民,张华瑾.一种新型模块化自重构机器人结构设计与仿真研究[J].机器人,2013,35(5):568-575,606.Cao Y J,Ge W M,Zhang H J.Structure design and simulation analysis of an innovative modular self-reconfigurable robot–360bot[J].Robot,2013,35(5):568-575,606.
[4]Chen I M,and Yang G L.Automatic model generation for modular reconfigurable robot dynamics[J].Journal of Dynamic Systems,Measurement and Control,1998,120(3):346-352.
[5]Meister E,Nosov E,and Paul L.Automatic onboard and online modelling of modular and self-reconfigurable robots[C]//2013 6th IEEE Conference on Robotics,Automation and Mechatronics(RAM):Manila,Philippines:IEEE,2013:91-96.
[6]Meister E,Alexander G,and Paul L.Dynamics and Control of Modular and Self-Reconfigurable Robotic Systems[J].International Journal on Advances in Intelligent Systems,2013,6(1 and 2):66-78
[7]Fei Y Q,Wang C Y.Self-Repairing Algorithm of Lattice-Type Self-Reconfigurable Modular Robots[J].Journal of Intelligent&Robotic Systems,2014,75(2):193-203.
[8]Mohammad R S,Mohammad H K,Mahmoodreza S.Robust fuzzy sliding mode control for tracking the robot manipulator in joint space and in presence of uncertainties.Robotica,2013,32(3):433-446.
[9]蔡锦达,李军华,张剑皓,李记岗.六轴工业机器人在线误差补偿方法的研究[J].控制工程,2014,21(5):638-642.Cai Jin-da,Li Jun-hua,Zhang Jian-hao,Li Ji-gang.Research on6-axis Industrial Robot Online Error Compensation[J].Control Engineering of China,2014,21(5):638-642.
[10]赵杰,魏延辉,蔡鹤皋.新型可重构机器人分布式控制方法的研究[J].哈尔滨工业大学学报,2008,40(1):39-42.Zhao J,Wei Y H,Ca H G.Distributed control method of new type reconfigurable modular robot[J].Journal of Harbin Institute of Technology,2008,40(1):39-42.
[11]李元春,陆鹏,赵博.可重构机械臂反演时延分散容错控制[J].控制与决策,2012,27(3):446-450.Li Y C,Lu P,Zhao B.Backstepping time delay decentralized fault-tolerant control for reconfigurable manipulators[J].Control and Decision,2012,27(3):446-450.
[12]Li Y C,Zhou F,Zhao B.Dynamic Output Feedback Based Active Decentralized Fault-Tolerant Control for Reconfigurable Manipulator with Concurrent Failures.Mathematical Problems in Engineering,2015(2015):1-14.
[13]Zhu M C,Li Y C.Decentralized adaptive fuzzy sliding,mode control for reconfigurable modular manipulators[J].International Journal of Robust and Nonlinear Control,2010,20(4):472-488.
[14]Zhao B,Wang Z Q,Qiao Y F.A combined backstepping terminal sliding mode algorithm based decentralized control scheme for reconfigurable manipulators[M].Advances in Reconfigurable Mechanisms and Robots I,Springer London,2012:657-668.
[15]Petkovi?M,Rapai?M R,Jeli?i?Z D,et al.On-line adaptive clustering for process monitoring and fault detection[J].Expert Systems with Applications,2012,39(11):10226-10235.
[16]杜佩君,张瑞锋.基于增广ESN的机器人轨迹跟踪控制[J].信息与控制,2013,42(4):443-448.Du P J,Zhang R F.Trajectory tracking control for robots based on Augmented ESN[J].Information and Control,2013,42(4):443-448.
[17]乃永强,李军.基于极限学习机的机械臂自适应神经控制[J].信息与控制,2015,44(3):257-262.Nai Y Q,Li J.Adaptive Neural Control of Manipulators Based on Extreme Learning Machine[J].Information and Control,2015,44(3):257-262.
[18]Huang G B,Zhu Q Y,Siew C K.Extreme learning machine:Theory and applications[J].Neurocomputing,2006,70(1):489-501.
[19]Huang G B,Wang D H,Lan Y.Extreme learning machines:A survey[J].International Journal of Machine Learning and Cybernetics,2011,2(2):107-122.
[20]王肖锋,张明路,葛为民.可重构机器人动力学自动建模研究[J].农业机械学报,2015,46(12):355-361,377.Wang X F,Zhang M L,Ge W M.Automatic Modeling of Dynamics for a Reconfigurble Robot[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(12):355-361,377.
[21]Narendra K S,Annaswamy A M.Stable adaptive systems[M].Courier Corporation,2012.
[22]?str?m K J,Wittenmark B.Adaptive control[M].Courier Corporation,2013.