5 research outputs found

    Robust nonlinear generalized predictive control of a permanent magnet synchronous motor with an anti-windup compensator

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    This paper presents a robust nonlinear generalized predictive control (RNGPC) strategy applied to a permanent magnet synchronous motor (PMSM) for speed trajectory tracking and disturbance rejection. The nonlinear predictive control law is derived by using a newly defined design cost function. The Taylor series expansion is used to carry out the prediction in a finite horizon. No information about the external perturbation and parameters uncertainties are needed to ensure the robustness of the proposed RNGPC. Moreover, to maintain the phase current within the limits using saturation blocks, a cascaded structure is adopted and an anti-windup compensator is proposed. The validity of the proposed control strategy is implemented on a dSPACE DS1104 board driving in real-time a 0.25 kW PMSM. Experimental results have demonstrated the stability, robustness and the effectiveness of the proposed control strategy regarding trajectory tracking and disturbance rejection

    Robust nonlinear generalized predictive control of a permanent magnet synchronous motor with an anti-windup compensator

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    This paper presents a robust nonlinear generalized predictive control (RNGPC) strategy applied to a permanent magnet synchronous motor (PMSM) for speed trajectory tracking and disturbance rejection. The nonlinear predictive control law is derived by using a newly defined design cost function. The Taylor series expansion is used to carry out the prediction in a finite horizon. No information about the external perturbation and parameters uncertainties are needed to ensure the robustness of the proposed RNGPC. Moreover, to maintain the phase current within the limits using saturation blocks, a cascaded structure is adopted and an anti-windup compensator is proposed. The validity of the proposed control strategy is implemented on a dSPACE DS1104 board driving in real-time a 0.25 kW PMSM. Experimental results have demonstrated the stability, robustness and the effectiveness of the proposed control strategy regarding trajectory tracking and disturbance rejection

    Robust nonlinear generalised predictive control for a class of uncertain nonlinear systems via an integral sliding mode approach

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    In this paper, a robust nonlinear generalised predictive control (GPC) method is proposed by combining an integral sliding mode approach. The composite controller can guarantee zero steady-state error for a class of uncertain nonlinear systems in the presence of both matched and unmatched disturbances. Indeed, it is well known that the traditional GPC based on Taylor series expansion cannot completely reject unknown disturbance and achieve offset-free tracking performance. To deal with this problem, the existing approaches are enhanced by avoiding the use of the disturbance observer and modifying the gain function of the nonlinear integral sliding surface. This modified strategy appears to be more capable of achieving both the disturbance rejection and the nominal prescribed specifications for matched disturbance. Simulation results demonstrate the effectiveness of the proposed approach

    Robust nonlinear predictive controller for permanent-magnet synchronous motors with an optimized cost function

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    A robust nonlinear predictive controller for permanent-magnet synchronous motors is proposed. The nonlinear predictive control law is formulated by optimizing a novel cost function. A key feature of the proposed control is that it does not require the knowledge of the external perturbation and parameter uncertainties to enhance the robustness. A zero steady-state error is guaranteed by an integral action of the controller. The stability of the closed-loop system is ensured by convergence of the output-tracking error to the origin. The proposed control strategy is verified via simulation and experiment. High performance with respect to speed tracking and current control of the motor has been demonstrated

    Robust cascaded nonlinear predictive control of a permanent magnet synchronous motor with antiwindup compensator

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    A nonlinear predictive control (NPC) scheme in a cascaded structure for a permanent magnet synchronous motor drive is proposed. Taylor series expansion is used to predict the system response over a finite horizon. As NPC cannot remove completely the steady-state error in the presence of mismatched parameters and external perturbation, a disturbance observer is used to estimate the offset caused by parametric uncertainties and the load torque variation. In addition, input constraints (restrictions on the magnitude) are considered in the synthesis of the disturbance observer, resulting in an equivalent cascaded proportional integral action with an antiwindup compensator. The validity of the proposed controller was tested via simulation and experiment. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection
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