DocumentCode :
2246182
Title :
Disturbance rejection in adaptive control for a class of nonlinear mechanical systems
Author :
Islam, S. ; Liu, P.X.
Author_Institution :
Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada
fYear :
2010
fDate :
6-9 July 2010
Firstpage :
762
Lastpage :
767
Abstract :
This paper presents hybrid control strategy for robust trajectory tracking control for a class of uncertain nonlinear mechanical systems. The design combines adaptive fuzzy system with robust adaptive control algorithm. Adaptive fuzzy system approximates unknown nonlinear system dynamics while a robustifying adaptive control term is used to cope with uncertainties due to the presence of external disturbance, modeling error and other unmodeled dynamical effects. Using the Lyapunov method, we first develop a stable hybrid controller by assuming that the system output and its derivatives are available for feedback control design. Then, an output feedback form of the position-velocity (state feedback) hybrid controller is proposed where the unknown velocity signal is replaced by the output of a model-free linear estimator. We prove that the tracking error bound under output feedback design can converge asymptotically to the tracking error bound achieved under the state feedback control design. Finally, the proposed method is implemented and evaluated on a 3-DOF Phantom™ medical mechatronics system to demonstrate the theoretical development.
Keywords :
Lyapunov methods; adaptive control; fuzzy control; mechatronics; nonlinear control systems; nonlinear dynamical systems; position control; robust control; state feedback; tracking; uncertain systems; 3-DOF Phantom medical mechatronics system; Lyapunov method; adaptive control term; adaptive fuzzy system; disturbance rejection; external disturbance; hybrid control strategy; model-free linear estimator; output feedback design; output feedback form; position velocity; robust adaptive control; robust trajectory tracking control; stable hybrid controller; state feedback control design; tracking error bound; uncertain nonlinear mechanical systems; unknown nonlinear system dynamics; unknown velocity signal; unmodeled dynamical effects; Adaptation model; Joints; Nonlinear dynamical systems; Output feedback; Robustness; State feedback; Uncertainty; 3-DOF PhantomTM Medical Mechatronics System; Fuzzy Systems; Robust Adaptive Control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Intelligent Mechatronics (AIM), 2010 IEEE/ASME International Conference on
Conference_Location :
Montreal, ON
Print_ISBN :
978-1-4244-8031-9
Type :
conf
DOI :
10.1109/AIM.2010.5695731
Filename :
5695731
Link To Document :
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