In this paper, we propose an online observer-based TakagiSugeno (TS) 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 TS 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 TS 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 Barbalats lemma and the better tracking performance are concluded. To illustrate the effectiveness of the proposed TS fuzzy controller and observer-design methodology, numerical simulation results are given in this paper.
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