Predictive control is a very wide class of controllers that have found rather recent application in the control of power converters. Research on this topic has been increased in the last years due to the possibilities of today's microprocessors used for the control. This paper presents the application of different predictive control methods to power electronics and drives. A simple classification of the most important types of predictive control is introduced, and each one of them is explained including some application examples. Predictive control presents several advantages that make it suitable for the control of power converters and drives. The different control schemes and applications presented in this paper illustrate the effectiveness and flexibility of predictive control.
In this paper, an improved finite control set-model predictive control (FCS-MPC) with an optimized weighting factor is presented. The main goal of this paper is reducing the torque ripples when the FCS-MPC is implemented by means of the twolevel inverter. For this purpose, the weighting factor is calculated via an optimization method. The optimization is based on dividing the control interval into two parts: active time for applying the active voltage vectors and zero time for applying the zero voltage. With this technique, the torque ripple is calculated as a function of weighting factor and it is optimized. The method is validated by simulations and experiments, using two-level inverter, at two speed regions (nominal speed and low speed). The results are compared with conventional FCS-MPC.
Field oriented control (FOC), direct torque control (DTC) and finite set model predictive control (FS-MPC) are different strategies for high performance electrical drive systems. FOC uses linear controllers and pulse width modulation (PWM) to control the fundamental components of the load voltages. On the other hand, DTC and FS-MPC are nonlinear strategies that generate directly the voltage vectors in the absence of a modulator. This paper presents all three methods starting from theoretic operating principles, control structures and implementation. Experimental assessment is performed to discuss their advantages and limitations in detail. As main conclusions of this work, it is affirmed that different strategies have their own merits and all meet the requirements of modern high performance drives.
This paper proposes a control strategy of finite control set model predictive torque control (FCS-MPTC) with a deadbeat (DB) solution for PMSM drives. By using a deadbeat solution, the process of selections of best switching vector is optimized. The predicted deadbeat voltage sector consisting of the desired voltage vector avoids the complete enumeration for testing all feasible voltage vectors, which relieves the big calculation effort of the traditional FCS-MPTC method. The proposed system is carried out experimentally both in steady state and in transient state. Index Terms-Torque control, optimization, model predictive control (MPC), deadbeat (DB), permanent magnet machines.
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