DocumentCode :
2773905
Title :
Design of Output Recurrent CMAC Backstepping Control System for Tracking Periodic Trajectories
Author :
Peng, Ya-Fu ; Lin, Ming-Hung ; Chong, Chao-Ming
Author_Institution :
Ching-Yun Univ., Chung-Li
fYear :
0
fDate :
0-0 0
Firstpage :
3108
Lastpage :
3113
Abstract :
An output recurrent cerebellar model articulation controller (ORCMAC) via the backstepping control technique is designed to control a linear ultrasonic motor (LUSM) for the tracking of periodic reference trajectories in this paper. The proposed ORCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) in efficient learning mechanism and dynamic response. In the ORCMAC backstepping control system, an adaptive ORCMAC is used to mimic an ideal backstepping control law and a compensated controller is designed to compensate for the difference between the ideal backstepping control law and the adaptive ORCMAC. Moreover, the Taylor linearization technique is employed to derive the linearized model of the ORCMAC. The adaptation laws of the control system are derived in the sense of Lyapunov stability analysis, so that the stability of the system can be guaranteed. Finally, the effectiveness of the proposed control system is verified by the experiments of LUSM motion control. Experimental results show that high-precision tracking response can be achieved by using the proposed ORCMAC backstepping control system.
Keywords :
Lyapunov methods; adaptive control; cerebellar model arithmetic computers; compensation; control system synthesis; linear systems; linearisation techniques; motion control; neurocontrollers; periodic control; position control; stability; tracking; ultrasonic motors; Lyapunov stability analysis; Taylor linearization; adaptive control; backstepping control; compensated controller; linear ultrasonic motor; linearized model; motion control; output recurrent cerebellar model articulation controller; periodic reference trajectory; tracking; Adaptive control; Adaptive systems; Backstepping; Control systems; Learning systems; Linearization techniques; Lyapunov method; Motion control; Programmable control; Trajectory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
Type :
conf
DOI :
10.1109/IJCNN.2006.247292
Filename :
1716521
Link To Document :
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