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A proportional–integral (PI) controller is the most frequently used control technique for adjustable speed-motor drives. The main advantage of a PI controller is its ability to ensure zero steady-state error under low-frequency disturbances and model uncertainties as long as the closed-loop system is stable. However, the transient performances, under a PI regulator, are highly dependent on the machine parameters, the external disturbances, and the input constraints. This brief proposes the design process of a novel PI speed controller that is capable of preserving almost the nominal transient performance under the parameter variation and external disturbances such as the load torque. The controller also suppresses the effect of input saturation that may occur because of the armature current limitation. Simulation and experimental tests are carried out to verify the validity of the proposed design process. The results revealed that the proposed PI controller is effective regarding nominal performance recovery and input constraints handling. [ABSTRACT FROM AUTHOR]

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 steady‐state performances are obtained. [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]

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]

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. [ABSTRACT FROM PUBLISHER]