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In this paper, we propose an online observer-based Takagi-Sugeno (T-S) fuzzy-output tracking-control technique and an improved generalized projection-update law for a class of general nonaffine nonlinear systems with unknown functions and external disturbances. First, a T-S fuzzy model and a mean-value estimation technique are adopted to approximate a so-called virtual linearized system (VLS) of a real system and avoiding a high-order derivative problem, respectively. Second, a novel design concept combining the T-S fuzzy controller, observer, and tuning algorithm by neural networks is proposed to improve system performance. After that, we also use improved generalized projection-update laws, which prevent parameters drift and confine adjustable parameters to the specified regions, to tune adjustable parameters. As a result, both the stability guarantee based on strictly positive real (SPR) Lyapunov theory and Barbalat's lemma and the better tracking performance are concluded. To illustrate the effectiveness of the proposed T-S fuzzy controller and observer-design methodology, numerical simulation results are given in this paper.
Date of Publication: June 2011