Title :
Optimal Critic Learning for Robot Control in Time-Varying Environments
Author :
Chen Wang ; Yanan Li ; Ge, Shuzhi Sam ; Tong Heng Lee
Author_Institution :
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
Abstract :
In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q-function-based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. The simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified.
Keywords :
end effectors; force control; learning (artificial intelligence); linear systems; optimal control; time-varying systems; trajectory control; Q-function; end effector; force regulation; impedance control; impedance parameters; interaction control; linear system; optimal critic learning; robot control; time-varying environment; trajectory tracking; Approximation methods; Equations; Force; Impedance; Optimal control; Robots; Time-varying systems; Critic learning; interaction control; optimal control; time-varying environment; time-varying environment.;
Journal_Title :
Neural Networks and Learning Systems, IEEE Transactions on
DOI :
10.1109/TNNLS.2014.2378812
