The stability of the proposed closed-loop system is assured based on the former term by forcing all poles of the dynamic error vector toward the origin within a short transient time, which guarantees a fast transient response of the control system by using the solution of an optimal control problem. Specifically the proposed deadbeat speed control law consists of a deadbeat stabilizing feedback control term and a compensation control term.

Unlike the conventional deadbeat controllers which are mainly used for deadbeat current control in the inner loop in a cascaded control structure, the proposed deadbeat controller is designed by incorporating a speed controller with a load torque disturbance observer. This paper investigates an observer-based deadbeat predictive speed controller (DBPSC) for a prototype surface-mounted permanent magnet synchronous motor (SPMSM) drive system. The results confirm the effectiveness of the proposed control method and its superiority over the other two methods. The performance of an interior permanent magnet synchronous motor drive under the proposed control method is evaluated and compared with those under the conventional predictive torque control method and a recently developed predictive torque control method without a weighting factor. Instead of directly using the motor parameters, the input and output data of the control system, i.e., voltage and current, are used for estimating three new coefficients employed in the predictions. Besides, an estimation scheme based on a data-driven model is adopted which enhances the robustness of the drive against parametric uncertainties.

As a result, the tuning of the weighting factor is avoided. In this paper, a predictive torque and flux control method is proposed for interior permanent magnet synchronous motor drives without a cost function.

Additionally, the model predictive control is degraded under the parametric uncertainties. The weighting factor should be well-tuned in accordance with the motor specifications and operating points. Finite control set model predictive torque and flux control of AC motor drives commonly selects optimum inverter switching states through a cost function with a required weighting factor.

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