Title :
Model reference learning approach and its applications to robot impedance control
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore
Abstract :
In this paper, a model reference learning control (MRLC) law is proposed for a class of nonlinear and time varying system. The robustness of the MRLC system to dynamics fluctuations, output measurement noises and errors in initial conditions is analyzed. The design method for analyzing the MRLC system is developed and sufficient conditions for the convergence are derived. An application of the MRLC to robotic impedance control is addressed and an impedance learning control (ImpLC) approach is presented
Keywords :
control system analysis; convergence; learning systems; nonlinear systems; robot dynamics; time-varying systems; convergence; dynamics; impedance learning control; model reference learning; nonlinear system; robot impedance control; robustness; sufficient conditions; time varying system; Design methodology; Fluctuations; Impedance; Noise measurement; Noise robustness; Nonlinear control systems; Nonlinear dynamical systems; Robots; Sufficient conditions; Time varying systems;
Conference_Titel :
Decision and Control, 1998. Proceedings of the 37th IEEE Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
0-7803-4394-8
DOI :
10.1109/CDC.1998.760763
