Browsing by Author "Kadjoudj, Mohamed"

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    Fuzzy approximation based model reference
    (IEEE, 2003) Goléa, Noureddine; Goléa, Amar; Kadjoudj, Mohamed
    Based on the universal approximation eapability of the Takagi-Seguno (TS) fuzzy systems, we present a solution to the model reference control of continuous-time nonlinear systems problem. Using the assumption that a fuzzy model exists for the considered nonlinear systems class, a direct TS fuzzy adaptive controller is designed to achieve the tracking objective. It is not required to estimate the fuzzy model, only its existence assumption is required. It is proved, using Lyapunov stability tools, that this adaptive scheme is asymptotically stable and the tracking error converges to zero. Simulation results illustrate the proposed algorithm performance.
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    Indirect fuzzy adaptive control
    (IEEE, 2002) Goléa, Noureddine; Goléa, Amar; Kadjoudj, Mohamed
    A new fuzzy indirect adaptive controller for continuous-time nonlinear systems, with a poorly understood dynamics, is developed. The proposed adaptive scheme uses a single Takagi-Seguno (TS) fuzzy model with few parameters to learn, which results in low implementation complexity and a fast learning rate. In addition, the use of TS fuzzy model permits the inclusion of a priori knowledge about the piant dynamics in terms of exact mathematical models or qualitative information. Using the hyperstahility approach, it is proved that this adaptive controller is globally asymptotically stable, and achieves asymptotic tracking of a stable reference model. The performance of the developed approach is illustrated with simulation results.
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    Indirect fuzzy adaptive control
    (IEEE, 2002) Goléa, Noureddine; Goléa, Amar; Kadjoudj, Mohamed
    A new fuzzy indirect adaptive controller for continuous-time nonlinear systems, with a poorly understood dynamics, is developed. The proposed adaptive scheme uses a single Takagi-Seguno (TS) fuzzy model with few parameters to learn, which results in low implementation complexity and a fast learning rate. In addition, the use of TS fuzzy model permits the inclusion of a priori knowledge about the piant dynamics in terms of exact mathematical models or qualitative information. Using the hyperstahility approach, it is proved that this adaptive controller is globally asymptotically stable, and achieves asymptotic tracking of a stable reference model. The performance of the developed approach is illustrated with simulation results.