Open AccessImpedance Controller Tuned by Particle Swarm Optimization for Robotic Arms
Author(s) -
Haifa Mehdi,
Olfa Boubaker
Publication year - 2011
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/45692
Subject(s) - particle swarm optimization , computer science , control theory (sociology) , controller (irrigation) , trajectory , cartesian coordinate system , impedance control , stability (learning theory) , robot , lyapunov function , electrical impedance , lyapunov stability , mathematics , algorithm , artificial intelligence , engineering , control (management) , physics , geometry , nonlinear system , astronomy , machine learning , quantum mechanics , agronomy , biology , electrical engineering
This paper presents an efficient and fast method for fine tuning the controller parameters of robot manipulators in constrained motion. The stability of the robotic system is proved using a Lyapunov-based impedance approach whereas the optimal design of the controller parameters are tuned, in offline, by a Particle Swarm Optimization (PSO) algorithm. For designing the PSO method, different index performances are considered in both joint and Cartesian spaces. A 3DOF manipulator constrained to a circular trajectory is finally used to validate the performances of the proposed approach. The simulation results show the stability and the performances of the proposed approach
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