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Rooted Tree Optimization Algorithm to Improve DTC Response of DFIM

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Abstract

In this paper, an integral-proportional (IP) controller is employed in speed loop control in direct torque control (DTC) of a doubly fed induction motor (DFIM). Using IP parameters obtained from classical tuning methods, such as pole placement method, Ziegler–Nichols, etc., has disadvantages like high undershoot and overshoot, slow settling time, etc. To overcome the drawbacks of the classical methods, a new approach in which the IP controller parameters are tuned by rooted tree optimization (RTO) algorithm minimizing a multi-objective function is presented. The proposed algorithm has been verified and tested in control system with a PID controller. It presents improvement in performance response of various processes of different order compared with techniques such as Ziegler–Nichols, Kitamori’s, Fuzzy-PID and Iterative Feedback Tuning. In addition, simulation results of direct torque control response of a DFIM with an IP controller designed using the RTO algorithm minimizing a multi-objective function show its effectiveness and better performance in speed response. Robustness test against parameter sensitivity for the proposed DTC-DFIM-RTO is verified under stator resistance variation.

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Acknowledgements

The authors would like to acknowledge support from Directorate General for Scientific Research and Technological Development (DGRSDT), Ministry of Higher Education and Scientific Research—Algeria.

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Authors and Affiliations

  1. LEVRES Laboratory, University of El Oued, 39000, El Oued, Algeria

    Youcef Bekakra, Yacine Labbi & Djilani Ben Attous

  2. Department of Electrical and Computer Engineering, University of Calgary, Calgary, AB, Canada

    Om P. Malik

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  1. Youcef Bekakra
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  2. Yacine Labbi
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Appendices

Appendix 1: DFIM Parameters

Rated values

4 kW, 220/380 V, 1440 rpm

Rated parameters

Rs = 1.2 Ω

Rr = 1.8 Ω

Ls = 0.1554 H

Lr = 0. 1568 H

M = 0.15 H

P = 2

Mechanical constants

J = 0.2 kg m2

f = 0.0 N m s/rad

 

Appendix 2: Nomenclature

DFIM

Vsα, Vsβ

Stator \(\alpha , \beta \) frame voltages

Vrα, Vrβ

Rotor \(\alpha , \beta \) frame voltages

isα, isβ

Stator \(\alpha , \beta \) frame currents

irα, irβ

Rotor \(\alpha , \beta \) frame currents

φsα, φsβ

Stator \(\alpha , \beta \) frame fluxes

φrα, φrβ

Rotor \(\alpha , \beta \) frame fluxes

Rsα, Rr

Stator and rotor resistances

Lsα, Lr

Stator and rotor inductances

M

Mutual inductance

\(\sigma \)

Leakage factor

Ts, Tr

Stator and rotor time-constant

\(\Omega \) r

Rotor speed

T e

Electromagnetic torque

T L

Load torque

J

Moment of inertia

f

Friction coefficient

p

number of pole pairs

ω r

Rotor angular speed

RTO

x new

New candidate

x best

Best solution

k

Candidate number

iter

Iteration

N

Population scale

upper

Upper limit

randn

Normal random number between [− 1, 1]

rand

Number between [0, 1]

R n

Rate of the random root

R r

Rate of the random root

R c

Rate of the continuous root

Acronyms

DFIM

Doubly Fed Induction Machine/Motor

DTC

Direct Torque Control

FOC

Field Oriented Control

IP

Integral Proportional

RTO

Rooted Tree Optimization

VC

Vector Control

2D/ 3D

Two / Three-dimensional

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Bekakra, Y., Labbi, Y., Ben Attous, D. et al. Rooted Tree Optimization Algorithm to Improve DTC Response of DFIM. J. Electr. Eng. Technol. 16, 2463–2483 (2021). https://doi.org/10.1007/s42835-021-00796-4

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