الأعمال الجامعية الأكاديمية

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Browsing الأعمال الجامعية الأكاديمية by Subject "Adaptive control"

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    Fuzzy adaptive control
    (IEEE, 2000) Goléa, N.; Benmahammed, K.; Goléa, A.
    This paper investigates a direct fuzzy adaptive control of continuous-time nonlinear systems. The proposed adaptive scheme uses a Takagi-Seguno (TS) fuzzy controller, which allows the inclusion of a priori information in terms of qualitative knowledge about the plant operating points or analytical conventional regulators (e.g., state feedback) for those operating points. Stability and robustness of this adaptive scheme are studied using the hyperstability tools. It is proven that this adaptive controller is globally asymptotically stable, and robust against external disturbance and approximation error. Fast tracking, low complexity and parameter convergence characteristics of the proposed approach are illustrated by simulation results.
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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.
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    Multivariable fuzzy adaptive
    (2002) Goléa, Noureddine; Goléa, Amar
    Based on Takagi-Seguno (TS) fuzzy eystems, we are used, this allows fast control update, which is limit Present a direct fuzzy model-following adaptive control for factor for L~~~~~~~ approach is used multivariable (MIMO) nonlinear systems. The use of the TS 8y6tems allows the inclusion of a priori information to establish the stability and robustness properties of the in terms of qualitative knowledge about the plant operat- proposed fuzzy adaptive scheme, in presence of approxiing peints or analytical conventional linear regulators. It is mation error, external disturbance and input gain variaproven, using Lyapunov stability, that this adaptive scheme tion, ~h~ results, for a two-li* robot model, is robust against external disturbance, approximation error and input gain variation, and achieves asymptotic tracking show that, this fuzzy adaptive control realizes a consistent of a stable reference model. The effectiveness of the pro- tracking performance under approximation error and exterposed fuzzy approach is demonstrated, by simulation, on a two-link robot model.
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    Multivariable fuzzy adaptive
    (2002) Goléa, Noureddine; Goléa, Amar
    Ba~ed on Takagi-Seguno (TS) fuzzy eystems, we are used, this allows fast control update, which is limit Present a direct fuzzy model-following adaptive control for factor for L~~~~~~~ approach is used multivariable (MIMO) nonlinear systems. The use of the TS 8y6tems allows the inclusion of a priori information to establish the stability and robustness properties of the in terms of qualitative knowledge about the plant operat- proposed fuzzy adaptive scheme, in presence of approxiing peints or analytical conventional linear regulators. It is mation error, external disturbance and input gain variaproven, using Lyapunov stability, that this adaptive scheme tion, ~h~ results, for a two-li* robot model, is robust against external disturbance, approximation error and input gain variation, and achieves asymptotic tracking show that, this fuzzy adaptive control realizes a consistent of a stable reference model. The effectiveness of the pro- tracking performance under approximation error and exterposed fuzzy approach is demonstrated, by simulation, on a two-link robot model.
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    Observer-based adaptive control of robot manipulators
    (ELSEVIER, 2008) Goléa, Noureddine; Goléa, Amar; Barra, Kamel
    This paper presents a fuzzy adaptive control suitable for motion control of multi-link robot manipulators with structured and unstructured uncertainties. When joint velocities are available, full state fuzzy adaptive feedback control is designed to ensure the stability of the closed loop dynamic. If the joint velocities are not measurable, an observer is introduced and an adaptive output feedback control is designed based on the estimated velocities. In the proposed control scheme, we need not derive the linear formulation of robot dynamic equation and tune the parameters. To reduce the number of fuzzy rules of the fuzzy controller, we consider the properties of robot dynamics and the decomposition of the uncertainties terms. The proposed controller is robust against uncertainties and external disturbance. Further, it is shown that required stability conditions, in both cases, can be formulated as LMI problems and solved using dedicated software. The validity of the control scheme is demonstrated by computer simulations on a two-link robot manipulator
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    Stable indirect fuzzy adaptive control
    (Elsevier, 2003) Goléa, N.; Goléa, A.; Benmahammed, K.
    This paper investigates new fuzzy model-based observer adaptive control for multi-input multi-output continuous-time nonlinear systems. The proposed adaptive scheme uses Takagi–Seguno (TS) fuzzy models to estimate the plant states and dynamics. Using stability arguments, it is shown that the proposed scheme is globally asymptotically stable. The observation and tracking errors are shown to converge asymptotically to zero, despite the presence ofexternal disturbances and approximation errors. The performance ofthe developed approach is illustrated, by simulation, on two-link robot model.