Abstract

To gain fast dynamic response, high performance, and good tracking capability, several control strategies have been applied to synchronous reluctance motors (SynRMs). In this paper, a nonlinear advanced strategy of speed predictive control (SPC) based on the finite control set model predictive control (FCS-MPC) is proposed and simulated for nonlinear SynRMs. The SPC overcomes the limitation of the cascaded control structure of the common vector control by employing a novel strategy that considers all the electrical and mechanical variables in one control law through a new cost function to obtain the switching signals for the power converter. The SynRM flux maps are known based on finite element method (FEM) analysis to take into consideration the effect of the nonlinearity of the machine. To clear the proposed strategy features, a functional and qualitative comparison between the proposed SPC, field-oriented control (FOC) with an anti-windup scheme, and current predictive control (CPC) with outer PI speed control loop is presented. For simplicity, particle swarm optimization (PSO) is performed to tune all the unknown parameters of the control strategies. The comparison features include controller design, dynamic and steady-state behaviors. Simulation results are presented to investigate the benefits and limitations of the three control strategies. Finally, the proposed SPC, FOC, and CPC have their own merits, and all methods encounter the requirements of advanced high-performance drives.

Highlights

  • The control of AC electric machines is one of the most important challenging issues in electrical engineering

  • current predictive control (CPC) strategy uses the error between the reference current and predicted currents based on a cost function to replace the inner PI controllers of the field-oriented control (FOC) strategy [1], while the control of the outer speed loop is still executed by the PI Controller as in Equation (8)

  • The unknown parameters of the control strategies are obtained through the particle swarm optimization (PSO) technique

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Summary

Introduction

The control of AC electric machines is one of the most important challenging issues in electrical engineering. Due to the increase of digital signal processing and power converters, in which fast dynamic response and uncomplex control are favored, researchers have been made for the nonlinear control strategies One of these is the finite control set model predictive control (FCS-MPC) [15,16,17]. In [26], model predictive speed control of permanent magnet synchronous motor (PMSM) based on the finite control set is proposed. The proposed SPC is replaced all PI controllers (inner and outer loops) by one control law called cost function to generate the signals for the converter. For ensuring the fair comparison between the three strategies, a set of parameters are kept constant such as simulation configuration parameters, sampling time for the prediction models, and PI controller parameters for generating the reference electromagnetic torque.

Drive Model
Inverter Model
Synchronous Reluctance Motor Modeling
Anti-Windup Scheme
Field-Oriented Control of Nonlinear SynRM
Current Predictive Control Strategy
The Proposed Speed Predictive Control
The Difference of Control Strategies
Particle Swarm Optimization
Simulation Results and Discussion
Conclusions
Full Text
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