Fuzzy Hybrid Force/Position Control of Dual-arm Robot Based on Genetic Algorithm
ZHOU Jun1, DING Xi-lun2
1. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China; 2. School of Mechanical Engineering and Automation, Beihang University, Beijing 100083, China
Abstract：Recent years,research on the technology of redundant dual-arm robot system for space-station operation gets considerable attention.Based on recent research conditions,coordinated control of the redundant dual-arm robot working inside the capsule is studied in this paper.According to the force on dual-arm robot during its coordinating task,a fuzzy hybrid force/position control strategy based on genetic algorithm is presented.The approach transforms force error of robot's end-effector into the position correction of robotic position controller through fuzzy control,so hybrid force/position control can be realized without changing the robotic position controller.The fuzzy control rules are optimized off line with genetic algorithm,and the collectivity crossover probability and the collectivity mutation probability use a self-adaptive control strategy to improve the arithmetic performance.Finally,through 3D simulation and experiment of force following in conveying a box by redundant dual-arm robot,the feasibility and applicability of the control strategy are verified.
[1] 丁希仑.容错冗余度双臂空间机器人系统的协调控制及遥操作研究[R].北京:北京航空航天大学,2003.Ding Xilun.Coordinating Control and Teleoperation of Fault tolerance Redundant Dual-arm Space Robot System[R].Beijing:Beihang University,2003.
[2] Xie H P.Real-time Cooperative Control of a Dual-arm Redundant Manipulator System[D].London,Canada:The University of Western Ontario,2000.
[3] Horspool K R.Cartesian-space Adaptive Control for Dual-arm Force Control Using Industrial Robots[D].Albuquerque,USA:The University of New Mexico,2003.
[4] 舒婷婷.操作臂机器人运动规划算法研究与实现[D].武汉:华中师范大学,2001.Shu Tingting.Design and Implementation on Robotic Manipulator Motion Planning Algorithm[D].Wuhan:Central China Normal University,2001.
[5] 蒋新松.机器人与工业自动化[M].石家庄:河北教育出版社,2003.405～407.Jiang Xinsong.Robot and Industrial Automation[M].Shijiazhuang:Hebei Education Press,2003.405～407.
[6] Lim J,Chyung D H.On a control scheme for two cooperating robot arms[A].Proceedings of the IEEE Conference on Decision and Control[C].Piscataway,NJ,USA:IEEE,1985.334～337.
[7] Zghal,H,Dubey,R V,Euler J A.Efficient gradient projection optimization for manipulators with multiple degree of redundancy[A].Proceedings of the IEEE International Conference on Robotics and Automation[C].Piscataway,NJ,USA:IEEE,1990.1006～1011.
[8] Chan T F,Dubey R V.A weighted least-norm solution based scheme for avoiding joint limits for redundant manipulators[A].Proceedings of the IEEE International Conference on Robotics and Automation[C].Piscataway,NJ,USA:IEEE,1993.395～402.
[9] 王秀俊,葛运建,肖波,等.人工智能在机器人力控制系统中的应用研究[J].华中科技大学学报(自然科学版),2004,32(Sup):65～67.Wang Xiujun,Ge Yunjian,Xiao Bo,et al.Application study of robotic force control system based on artificial intelligence[J].Journal of Huazhong University of Science and Technology(Nature Science Edition),2004,32(Sup):65～67.
[10] 孙增圻,张再兴,邓志东.智能控制理论与技术[M].北京:清华大学出版社,1997.52～62.Sun Zeng-qi,Zhang Zai-xing,Deng Zhi-dong.Intelligent Control Theory and Technology[M].Beijing:Tsinghua University Press,1997.52～62.
[11] Srinivas M,Patnalk L M.Adaptive probabilities of crossover and mutation in genetic algorithms[J].IEEE Transacitions on Systems,Man and Cybernetics,1994,24(4):656～667.
[12] 王蕾,沈庭芝,招杨.一种改进的自适应遗传算法[J].系统工程与电子技术,2002,24(5):75～78.Wang Lei,Shen Ting-zhi,Zhao Yang.An improved adaptive genetic algorithm[J].Systems Engineering and Electronics,2002,24(5):75～78.
