HGO-based decentralised indirect adaptive fuzzy control for a class of large-scale nonlinear systems

Abstract

In this article, a novel high gain observer (HGO)-based decentralised indirect adaptive fuzzy controller is developed for a class of uncertain affine large-scale nonlinear systems. By the combination of fuzzy logic systems and an HGO, the state variables are not required to be measurable. The proposed feedback and adaptation mechanisms guarantee that each subsystem is able to adaptively compensate for interconnections and disturbances with unknown bounds. It is ascertained using a singular perturbation method that all the signals of the closed-loop large-scale system stand uniformly ultimately bounded and the tracking errors converge to tunable neighbourhoods of the origin. Simulation results of correlated double inverted pendulums substantiate the effectiveness of the proposed controller.

Keywords:

• large-scale system
• adaptive control
• fuzzy control
• output feedback
• decentralised control
• singular perturbation method

Acknowledgements

This project was supported by the National Natural Science Foundation of China (61104014, 50808025), the Open Fund of the Key Laboratory of Highway Engineering (Changsha University of Science & Technology), the Ministry of Education (kfj110101), the National Science and Technology Support Programme of China (2007BAK23B03), the China Postdoctoral Science Foundation (20110491270, 20100471231), the Natural Science Foundation of Hunan Province of China (09JJ9012), the Fok Ying Tung Education Foundation of China (122013) and the Scientific Research Fund of Hunan Provincial Education Department of China (08A003).