Parameter Estimation of DC Motor using Adaptive Transfer Function Based on Nelder-Mead Optimisation

Nayak, Byamakesh; Sahu, Sangeeta; Choudhury, Tanmoy Roy

doi:10.11591/ijeecs.v9.i3.pp696-702

Cited by 9 publications

(13 citation statements)

References 7 publications

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“…Taking into account a large number of works devoted to development of a model of pulsating current traction electric motor demanded models are those that take into account nonlinearity of magnetization characteristics and occurrence of eddy currents and magnetic losses in the motor magnetic circuit. This can be confirmed by works on approximation of magnetization characteristic [1,2] and simulation of pulsating current traction electric motors of pulsating current taking into consideration influence of eddy currents on the nature of the magnetization curve [3]. Simulation models obtained in the result of applying these methods give an opportunity to determine with high accuracy such traction motor parameters as motor shaft speed at any load, currents flowing in traction motor circuits, electromotive force (EMF) generated by the motor, but taking into account all power losses in traction motor.…”

mentioning

confidence: 56%

“…When modeling a direct current traction motor (DCM) of series excitation the main problem is to reproduce the dependence of magnetic flux on currents of field winding and armature currents; and this implies presence of load characteristics. In the work by [1] the authors propose to use universal magnetization curve for DCM of series excitation, and on the basis of universal magnetic characteristic to calculate universal expressions for the intrusive parameters of direct current traction electric machines and those of pulsating current traction motors. Since the universal magnetic characteristic is built for machines working under load, in order to reduce the error of approximation the author proposed to approximate the universal magnetic characteristic by means of two functions: magnetomotive force of the field winding and magnetomotive force of the armature reaction.…”

mentioning

confidence: 99%

“…These processes significantly affect the change of magnetic flux in the motor steel and, accordingly, the nature of electromagnetic processes occurring in it. In works by [1,2] the influence caused by eddy currents in the motor magnetic circuit on the change of magnetic flux is not taken into account. Solution of this problem can be found in the work by [3].…”

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confidence: 99%

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Model of pulsating current traction motor taking into consideration magnetic losses in steel

Goolak

Riabov

Tkachenko

et al. 2021

Electrical Engineering & Electromechanics

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The aim of the work is to develop a mathematical model of the traction motor of the pulsating current of an electric locomotive taking into account the magnetic losses in the motor steel to determine the starting parameters depending on the voltage of the armature winding. Methodology. Mathematical modeling of electromagnetic processes in a traction motor of pulsating current is applied taking into account the nonlinear nature of the armature inductance, the inductance of the excitation winding and the nonlinear nature of the universal magnetic characteristic. The magnetic losses in the steel of the traction motor were taken into account by establishing the dependence of these losses on the frequency of reversal, the magnetic flux in the magnetic circuit of the motor and the geometric dimensions of the motor. Results. The mathematical model of calculation of starting parameters of the traction engine of the pulsating current of the traction drive of the electric locomotive of alternating current taking into account the equation of instantaneous value of losses in engine steel is developed. The dynamic characteristics of the traction motor with pulsating current are obtained. It allows to investigate starting parameters of the traction engine on the basis of the received mathematical model and to design elements of the traction drive of the electric locomotive according to the specification, to choose optimum design parameters. Originality. For the first time a comprehensive study of the pulsating current traction motor was carried out taking into account the nonlinear nature of the armature inductance, excitation winding inductance and nonlinear nature of the universal magnetic characteristic and taking into account the magnetic losses in the motor steel. Practical significance. The model of the traction motor of pulsating current taking into account losses in steel of the engine on the basis of the carried-out calculation is developed. Experimental studies have confirmed the adequacy of the model, which allows to apply the obtained model to develop a mathematical model of an AC electric locomotive to study the electrodynamic processes in it at different modes of operation of the electric locomotive.

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confidence: 56%

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confidence: 99%

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Model of pulsating current traction motor taking into consideration magnetic losses in steel

Goolak

Riabov

Tkachenko

et al. 2021

Electrical Engineering & Electromechanics

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“…In many areas of industrial control, it is hard to get the ideal value using the ZN method. The Nelder-Mead (NM) simplex algorithm [4] is intended to solve the traditional unrestricted optimization issues to reduce a provided nonlinear function such as PID tuning.…”

Section: Introductionmentioning

confidence: 99%

Identification and Speed Control of DC Motor Using Fractional Order PID: Microcontroller

El‐Saadawi¹,

Gouda²,

Elhosseini³

et al. 2020

EJECE

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This paper uses Fractional-order PID control (FOPID) to control the speed of the DC motor. FOPID is more flexible and confident in controlling control higher-order systems compared to classical PID. In this work, the FOPID controller tuning is carried out using different methods ranging from classical techniques to most recent heuristic methods are Fractional Grey wolf Optimization and Nelder-Mead. Moreover, parameter estimation of real-world DC motor is carried out experimentally using Matlab/Simulink interfaced to an Arduino Uno board. The feasibility of FOPID is demonstrated through applications to well-known DC motor case study and the estimated DC motor. Based on ISE, ITE, and ISTE performance measures, the proposed approach provide less settling time, rise time and comparable overshoot compared with existing literature approaches. A robustness assessment with differences in the DC motor components is performed. Simulation finding provide validation of the suggested work and the FOPID controller effectiveness as compared to classical PID controller in terms of robustness and control effect.

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“…Grey Wolf Optimization [21] and Bio -Inspired Optimization Algorithm [22] is used for parameter estimation of PMDC coreless micro-motor. The dc motor parameter is evaluated accurately by the recently published Flower Pollination Algorithm (FPA) [23] and Nelder -Mead Optimisation [24].…”

Section: Introductionmentioning

confidence: 99%

Parameter estimation of DC motor through whale optimization algorithm

Nayak¹,

Sahu²

2019

IJPEDS

Self Cite

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This article estimates the unknown dc motor parameters by adapting the adaptive model with the reference model created by experimental data onto armature current and speed response from separately excited dc motor .The field flux dynamics, which is usually ignored, is included to model the dynamics of the motor. The block diagram including the flux dynamics and model parameters is considered as the adaptive model. The integral time square error between the instant experimental data and the corresponding adaptive model data is taken as cost function. The Whale optimization algorithm is used to minimize the cost function. Additionally, to improve the performances of optimization algorithm and for accurate result, the experimental data is divided into three intervals which form the three inequality constraints. A fixed penalty value is added to the cost function for violating these constraints. The effectiveness of estimation with two different methods is validated by convergence curve.

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Parameter Estimation of DC Motor using Adaptive Transfer Function Based on Nelder-Mead Optimisation

Cited by 9 publications

References 7 publications

Model of pulsating current traction motor taking into consideration magnetic losses in steel

Model of pulsating current traction motor taking into consideration magnetic losses in steel

Identification and Speed Control of DC Motor Using Fractional Order PID: Microcontroller

Parameter estimation of DC motor through whale optimization algorithm

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