Title :
Adaptive Dynamic Surface Control of Flexible-Joint Robots Using Self-Recurrent Wavelet Neural Networks
Author :
Yoo, Sung Jin ; Park, Jin Bae ; Choi, Yoon Ho
Author_Institution :
Dept. of Electr. & Electron. Eng., Yonsei Univ., Seoul
Abstract :
A new method for the robust control of flexible-joint (FJ) robots with model uncertainties in both robot dynamics and actuator dynamics is proposed. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self-recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides the ability to overcome the "explosion of complexity" problem in backstepping controllers. The SRWNNs are used to observe the arbitrary model uncertainties of FJ robots, and all their weights are trained online. From the Lyapunov stability analysis, their adaptation laws are induced, and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a three-link FJ robot are utilized to validate the good position tracking performance and robustness against payload uncertainties and external disturbances of the proposed control system
Keywords :
Lyapunov methods; actuators; adaptive systems; closed loop systems; flexible manipulators; manipulator dynamics; recurrent neural nets; robust control; wavelet transforms; Lyapunov stability analysis; adaptive actuator dynamic surface control; closed-loop system; flexible-joint robot; self-recurrent wavelet neural network; Actuators; Adaptive control; Control systems; Explosions; Neural networks; Programmable control; Robot control; Robust control; Surface waves; Uncertainty; Dynamic surface control (DSC); flexible-joint robots; robust control; self-recurrent wavelet neural network (SRWNN);
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2006.875869
