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The design and the experimental validation of a continuous-time model predictive control (CTMPC) for a permanent magnet synchronous motor (PMSM) drive with disturbance decoupling is discussed. The CTMPC approach uses Taylor series expansion to derive a closed-form solution to the problem of model predictive control even though the system behaviour is described by a non-linear model. This type of controller requires an exact knowledge of the system model to guarantee an accurate prediction of the system behaviour, while the PMSM is usually subjected to model uncertainties and external disturbances such as the load torque. Moreover, in the proposed approach, the predicted speed tracking error is directly used to determine the required voltage command without the need for a cascaded control scheme. As a result, the load torque is seen as unmatched disturbance which makes exact disturbance decoupling more challenging. To overcome such a problem, a non-linear disturbance observer is designed and combined with the CTMPC method to enhance the prediction accuracy under parameter variation and unknown load torque. The feasibility of the proposed approach is experimentally investigated, and good transient and steadystate performances are obtained. [ABSTRACT FROM AUTHOR]

This paper presents the design, implementation, and performance testing of a nonlinear proportional-integral (PI) predictive controller for a grid-tied inverter used in photovoltaic systems. A conventional cascade structure is adopted to design the proposed controller, where the outer loop is used to regulate the dc-link voltage, and the inner loop is designed as a current controller for adjusting the active and reactive powers injected into the grid. For each loop, the controller is derived based on combining a continuous-time nonlinear model predictive control and nonlinear disturbance observer techniques. It turns out that the composite controller reduces to a nonlinear PI controller with a predictive term that plays an important role in improving tracking performance. The salient feature of the proposed approach is its ability to approximately preserve the nominal tracking performance during the startup phase. Both simulation and experimental results are provided to demonstrate the effectiveness of the proposed approach in terms of nominal performance recovery, disturbance rejection, and current control. [ABSTRACT FROM AUTHOR]

A predictive direct torque controller (PDTC) for induction motors (IM) is proposed. It combines the direct torque control (DTC) and the predictive control (PC), and uses a predictive switching table to enhance the overall performance of the motor. A new type of PC is adopted for speed regulation with the use of a load torque observer, the torque being considered an unknown perturbation. A Kalman filter (KF) is used for reliable flux estimation. The validity of the proposed controller was experimentally confirmed on a rapid control prototyping station. The obtained results have proven superiority of the proposed control with respect to the speed trajectory tracking, torque and flux dynamic responses, and disturbance rejection. Also, a lower current distortion was observed with PDTC, in comparison with the regular DTC, due to increased mean inverter switching frequency. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

This paper presents a robust continuous nonlinear model predictive control (CNMPC) for a grid-connected photovoltaic (PV) inverter system. The objective of the proposed approach is to control the power exchange between the grid and a PV system, while achieving unity power factor operation. As the continuous nonlinear MPC cannot completely remove the steady-state error in the presence of disturbances, the nonlinear disturbance observer-based control is adopted to estimate the offset caused by parametric uncertainties and external perturbation. The stability of the closed-loop system under both nonlinear predictive control and disturbance observer is ensured by convergence of the output-tracking error to the origin. The proposed control strategy is verified using a complete laboratory-scale PV test-bed system consisting of a PV emulator, a boost converter, and a grid-tied inverter. High performance with respect to dc-link voltage tracking, grid current control, disturbance rejection, and unity power factor operation has been demonstrated. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]