Model Predictive Direct Torque Control—Part I: Concept, Algorithm, and Analysis

Geyer, Tobias; Papafotiou, Georgios; Morari, Manfred

doi:10.1109/tie.2008.2007030

Cited by 699 publications

(316 citation statements)

References 20 publications

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“…Unlike in DTC the effect of each possible switch state is calculated and evaluated to obtain the optimal switch sequence. more information on predictive torque and flux control can be found in the literature [3], [10]. In this application a 2-level inverter is used as shown in figure 8.…”

Section: A Application: Flux and Torque Control For Induction Motormentioning

confidence: 99%

Design choices for the prediction and optimization stage of finite-set model based predictive control

Vyncke

Thielemans

Dierickx

et al. 2011

2011 Workshop on Predictive Control of Electrical Drives and Power Electronics

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Abstract-The interest in applying model-based predictive control (MBPC) for power-electronic converters has grown tremendously in the past years. This is due to the fact that MBPC allows fast and accurate control of multiple controlled variables for hybrid systems such as a power electronic converter and its load. As MBPC is a family of possible controllers rather than one single controller, several design choices are to be made when implementing MBPC. In this paper several conceptual possibilities are considered and compared for two important parts of online Finite-Set MBPC (FS-MBPC) algorithm: the cost function in the optimizations step and the prediction model in the prediction step. These possibilities are studied for two different applications of FS-MBPC for power electronics. The cost function is studied in the application of output current and capacitor voltage control of a 3-level flyingcapacitor inverter. The aspect of the prediction model is studied for the stator flux and torque control of an induction machine with a 2-level inverter. The two different applications illustrate the versatility of FS-MBPC. In the study concerning the cost function firstly the comparison is made between quadratic and absolute value terms in the cost function. Comparable results are obtained, but a lower resource usage is obtained for the absolute value cost function. Secondly a capacitor voltage tracking control is compared to a control where the capacitor voltage may deviate without cost from the reference up to a certain voltage. The relaxed cost function results in better performance. For the prediction model both a classical, parametric machine model and a back propagation artificial neural network are applied. Both are shown to be capable of a good control quality, the neural network version is much more versatile but has a higher computational burden. However, the number of neurons in the hidden layer should be suffciently high. All studied aspects were verified with experimental results and these validate the simulation results. Even more important is the fact that these experiments prove the feasibility of implementing online finite-set MBPC in an FPGA for both applications.

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Section: A Application: Flux and Torque Control For Induction Motormentioning

confidence: 99%

Design choices for the prediction and optimization stage of finite-set model based predictive control

Vyncke

Thielemans

Dierickx

et al. 2011

2011 Workshop on Predictive Control of Electrical Drives and Power Electronics

View full text Add to dashboard Cite

show abstract

“…Variant types of this control strategy have been used for power conversion and motor drive control that mainly associated with modulation techniques [7][8][9][10][11]. The application of this family of nonlinear control techniques for torque and flux control in induction machines (IMs) has received attention from researchers due to the technique's qualities of fast dynamic torque response, low torque ripple, and reduced switching frequency [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study Between Direct Torque Control and Predictive Torque Control for Axial Flux Permanent Magnet Synchronous Machines

Siami¹,

Gholamian²,

Yousefi³

2013

Journal of Electrical Engineering

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This paper presents a comparative study between direct torque control (DTC) and predictive torque control (PTC) of Axial Flux Permanent magnet Machines (AFPM). In conventional DTC method for permanent magnet machines, only six actives voltage vectors of inverter are used to control torque and flux of machine. But in predictive torque control, in addition to six active voltage vectors, zero voltage vectors are used to control machine. So number of voltage vectors to control AFPM increases that leads to lower ripple of torque and flux. In predictive torque control, the response of torque and flux are computed for all possible switching states of inverter at every sample time according to discrete time model of machine, and then the switching state that optimizes ripple of torque and flux, will be applied in next discrete-time interval. Simulation results which compare the results of implementation of both methods and confirm the good performance of the proposed predictive torque control are presented.

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“…The algorithms are sensitive to parameter changes. Prediction includes accurate calculations of controlled parameters (flux and torque) [13] as well as determination of their values in one or several steps ahead [14,15,16].…”

Section: Introductionmentioning

confidence: 99%

Improved Algorithms of Direct Torque Control Method

Sikorski

Korzeniewski

2013

Automatika

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In the paper a new way of DTC control method analysis to explain flux and current distortion at a low speed of motor operation is discussed. As a result, a new DTC-δ algorithm is proposed. It is important that the DTC-δ algorithm uses the same switching table as the DTC method. The modified DTC algorithms are free from the disadvantages of the conventional DTC method i.e. hexagonal flux and strongly deformed current at a low speed range. The dynamical properties of the new algorithms are similar to the conventional DTC method. The correctness of the proposed methods has been confirmed by laboratory investigations.Key words: Direct torque control (DTC), Induction motor drives, Variable-speed drives Unaprije eni algoritmi za izravno upravljanje momentom. Ovaj se rad bavi novim načinom analize izravnog upravljanja momentom (DTC) radi objašnjenja distorzije toka i struje na malim brzinama vrtnje motora. Kao rezultat, predložen je novi DTC-δ algoritam. Pritom je značajno da novi DTC-δ algoritam koristi istu tablicu prekapčanja kao i DTC metoda. Modificirani DTC algoritmi su bez nedostataka karakterističnih za konvencionalne DTC metode, poput heksagonalnog toka i izrazito izobličene struje pri niskim brzinama. Dinamička svojstva novih algoritama su slična konvencionalnoj DTC metodi. Predložene metode su potvr ene laboratorijskim ispitivanjima.Ključne riječi: izravno upravljanje momentom (DTC), elektromotorni pogoni s kaveznim strojem, pogoni s promjenjivom brzinom vrtnje

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Model Predictive Direct Torque Control—Part I: Concept, Algorithm, and Analysis

Cited by 699 publications

References 20 publications

Design choices for the prediction and optimization stage of finite-set model based predictive control

Design choices for the prediction and optimization stage of finite-set model based predictive control

A Comparative Study Between Direct Torque Control and Predictive Torque Control for Axial Flux Permanent Magnet Synchronous Machines

Improved Algorithms of Direct Torque Control Method

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