Non‐linear MPC for winding loss optimised torque control of anisotropic PMSM

Schnurr, Christoph; Hohmann, Sören; Kolb, Johannes

doi:10.1049/joe.2018.8143

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…In addition to fieldoriented control and direct torque control, model predictive control (MPC) has been studied and explored by more and more scholars. MPC [5][6][7][8][9] is mainly divided into continuous predictive control [10] and finite control set-model predictive control [11][12][13][14][15][16][17] (FCS-MPC). Compared with continuous predictive control, FCS-MPC combines the motor model with the switch state of the inverter.…”

Section: Introductionmentioning

confidence: 99%

Robust model predictive current control without dead‐zone compensation

Zhang

Liu

2020

IET Electric Power Applications

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To solve the problems of large steady‐state errors, high harmonic components and poor robustness of traditional current model prediction, a novel three‐vector model predictive current control for permanent magnet synchronous motor is presented in this study. The vectors operating time is calculated with the combination of current increment and the unconventional modulation method is adopted to generate duty cycle containing dead zone. Adopting the current command correction link, the current deviation caused by inaccuracy parameter is reduced. Proved by experiment, novel control system not only the current steady‐state error and current harmonic component are reduced, but also the parameter robustness is enhanced.

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Section: Introductionmentioning

confidence: 99%

Robust model predictive current control without dead‐zone compensation

Zhang

Liu

2020

IET Electric Power Applications

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“…In addition to [13] saturation effects of the main inductance are taken into account and a simplified suboptimal solution avoiding an online optimization is presented. Recently a quite different control scheme for a permanent magnet synchronous machine was given in [15]. Based on an linearized parameter dependent mathematical model for the motor which also includes magnetic saturation, a model predictive control concept is developed.…”

Section: Introductionmentioning

confidence: 99%

Induction Machine Control for a Wide Range of Drive Requirements

2019

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In this paper, a method for induction machine (IM) torque/speed tracking control derived from the 3-D non-holonomic integrator including drift terms is proposed. The proposition builds on a previous result derived in the form of a single loop non-linear state controller providing implicit rotor flux linkage vector tracking. This concept was appropriate only for piecewise constant references and assured minimal norm of the stator current vector during steady-states. The extended proposition introduces a second control loop for the rotor flux linkage vector magnitude that can be either constant, programmed, or optimized to achieve either maximum torque per amp ratio or high dynamic response. It should be emphasized that the same structure of the controller can be used either for torque control or for speed control. Additionally, it turns out that the proposed controller can be easily adapted to meet different objectives posed on the drive system. The introduced control concept assures stability of the closed loop system and significantly improves tracking performance for bounded but arbitrary torque/speed references. Moreover, the singularity problem near zero rotor flux linkage vector length is easily avoided. The presented analyses include nonlinear effects due to magnetic saturation. The overall IM control scheme includes cascaded high-gain current controllers based on measured electrical and mechanical quantities together with a rotor flux linkage vector estimator. Simulation and experimental results illustrate the main characteristics of the proposed control.

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