The robotic impedance controller multi-objective optimization design based on Pareto optimality

doi:10.1007/978-3-319-42297-8_39

	The robotic impedance controller multi-objective optimization design based on Pareto optimality
	Li, Erchao
	2016
会议日期	August 2, 2016 - August 5, 2016
会议地点	Lanzhou, China
关键词	Controllers Design Intelligent computing Manipulators Optimal systems Pareto principle Robotics Adjustment rules Dynamic performance High complexity Impedance control Impedance controllers Pareto optimal solutions Pareto-optimality Satisfactory solutions
卷号	9773
DOI	10.1007/978-3-319-42297-8_39
页码	413-423
英文摘要	The robotic impedance control is currently one of the main control methods, its main characteristic is that it can make manipulators move to the appointed position quickly and accurately. Due to the high complexity of the robot system, to adjust the impedance controller parameter is always difficult. The impedance controller multi-objective optimization design method is proposed, taking dynamic performances as the optimization objectives, a multi-objective optimization algorithm based on Pareto optimality is applied to the optimal design, obtain Pareto optimal solutions, and get some initial impedance controller adjustment rules, the satisfactory solution is selected in Pareto-optimal solutions according to the requirements of the present system. Simulation results indicate the effectiveness of the proposed algorithm. © Springer International Publishing Switzerland 2016.
会议录	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
会议录出版者	Springer Verlag
语种	英语
ISSN号	03029743
内容类型	会议论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/117214]
专题	电气工程与信息工程学院
作者单位	College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou; 730050, China
推荐引用方式 GB/T 7714	Li, Erchao. The robotic impedance controller multi-objective optimization design based on Pareto optimality[C]. 见:. Lanzhou, China. August 2, 2016 - August 5, 2016.