Technical Notes and Correspondence
International Journal of Control, Automation and Systems 2009; 7(4): 681-690
Published online August 1, 2009
https://doi.org/10.1007/s12555-009-0420-4
© The International Journal of Control, Automation, and Systems
Observer-based Direct Adaptive Fuzzy Control of Uncertain Nonlinear Systems and Its Applications
A direct adaptive fuzzy control algorithm is developed for a class of uncertain SISO nonlinear systems. In this algorithm, it doesn’t require to assume that the system states are measurable. Therefore, it is needed to design an observer to estimate the system states. Compared with the numerous alternative approaches with respect to the observer design, the main advantage of the developed algorithm is that on-line computation burden is alleviated. It is proven that the developed algorithm can guarantee that all the signals in the closed-loop system are uniformly ultimately bounded and the tracking error converges to a small neighborhood around zero. The simulation examples validate the feasibility of the developed algorithm.
Keywords Adaptive fuzzy control, nonlinear systems, uncertainties.
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Technical Notes and Correspondence
International Journal of Control, Automation and Systems 2009; 7(4): 681-690
Published online August 1, 2009 https://doi.org/10.1007/s12555-009-0420-4
Copyright © The International Journal of Control, Automation, and Systems.
Observer-based Direct Adaptive Fuzzy Control of Uncertain Nonlinear Systems and Its Applications
Yan-Jun Liu, Shao-Cheng Tong, Wei Wang, and Yong-Ming Li
Liaoning University of Technology, China
Abstract
A direct adaptive fuzzy control algorithm is developed for a class of uncertain SISO nonlinear systems. In this algorithm, it doesn’t require to assume that the system states are measurable. Therefore, it is needed to design an observer to estimate the system states. Compared with the numerous alternative approaches with respect to the observer design, the main advantage of the developed algorithm is that on-line computation burden is alleviated. It is proven that the developed algorithm can guarantee that all the signals in the closed-loop system are uniformly ultimately bounded and the tracking error converges to a small neighborhood around zero. The simulation examples validate the feasibility of the developed algorithm.
Keywords: Adaptive fuzzy control, nonlinear systems, uncertainties.
Vol. 23, No. 3, pp. 683~972
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