Indirect adaptive fuzzy control scheme based on observer for nonlinear systems: A novel SPR-filter approach

International audienceIn this paper, a novel fuzzy indirect adaptive controller based on observer for uncertain nonlinear perturbed systems is proposed. A tracking-error observer is introduced to resolve the problem of the unavailability of state variables. Adaptive fuzzy systems are employed to approximate the unknown smooth nonlinear functions. The control system is augmented by a low-pass filter designed to meet a SPR condition of a transfer function of the observation error dynamics. The SPR condition is used in the Lyapunov stability analysis to construct the adaptation laws using only available measurements (i.e. the output observation error and the output tracking error). The main contributions of this paper lie in the following: (a) The SPR-filter approach used here avoids the filtering of the fuzzy basis functions. (b) Unlike in the previous works, the stability analysis is rigorously proven by using a SPR-based Lypunov approach. Finally, numerical simulation results are presented to verify the feasibility and effectiveness of the proposed controller

Adaptive fuzzy vector control for a doubly-fed induction motor

International audienceAbstract This paper presents a new adaptive fuzzy vector controller (AFVC) to handle the torque and speed tracking problem of a doubly-fed induction motor (DFIM) as an alternative to classical PI based vector control method generally used for its simplicity. However, the control performance of DFIM is still influenced by the variations of the parameters, the external load disturbances and perturbations in practical applications. Then, it is difficult to achieve high control performances of DFIM by using conventional PI-type control techniques. The proposed AFVC scheme uses adaptive fuzzy systems to reasonably approximate the uncertain dynamics appearing in the DFIM, relaxing thereby the usual modeling requirement about the DFIM dynamics. Of fundamental interest, it is shown that all the closed-loop signals are bounded and the tracking errors exponentially converge to a residual set. Probing simulation results are given to emphasize the effectiveness of the proposed AFVC system with respect to the usual feedback linearization based vector control (FLVC) system

Microstructural characterization and determination of adhesion of 100Cr6 steel coatings thermally sprayed on a 35CrMo4 substrate

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