Improvement of vector control of Dual Star Induction drive using synergetic approach

Guermit, Hossine; Kouzi, Katia

doi:10.1109/ssd.2017.8167006

Cited by 6 publications

(5 citation statements)

References 7 publications

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“…Studying the works of Gao A., Chen H., Vögeling H., Lee Yongwei, Pozin G.M., Pryschep L.G., Stroy A.F., Takakura, Terence Belvins, Tkachenko V.A. and other scientists, experts proved that it is necessary to improve the existing microclimate control systems in the under-cover greenhouse facilities towards their comprehensiveness in terms of managerial decision making in order to come to a compromise between the energy expenditures and quality of the products [13][14][15][16][17][18][19][20][21][22][23][24]. Control systems were developed that provide intelligent formation of control strategies based on information received from a mobile robot [5,26].…”

Section: Related Workmentioning

confidence: 99%

Intellectual Scenario-synergetic Control of the Humidity and Temperature Regime of the Greenhouse Facilities

Polishchyk¹,

Lysenko²,

Osadchiy³

et al. 2022

IJC

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The article substantiates the management of the humidity and temperature regime of greenhouse complexes on the basis of a scenario-synergetic approach. The scenarios for controlling the temperature and humidity conditions in the greenhouse using the approach of fuzzy neural networks are formed. The structure of an automated control system for technological processes is developed, which provides automated collection and processing of information for the implementation of control actions in order to improve the efficiency of the greenhouse complex on the basis of a scenario-synergetic approach. The corresponding fuzzy neural networks are synthesized for a synergistic assessment of the interaction of technological parameters. Estimation of the root-mean-square error in the synthesis of fuzzy neural networks confirms the possibility of their use for the synergistic formation of scenarios for controlling the temperature and humidity regime in greenhouses to reveal the presence of a synergistic effect. Production rules for scenario management of temperature and humidity conditions are formed. It is shown that the use of fuzzy neural networks for the formation of scenarios for controlling the humidity and temperature regime provides the possibility of obtaining the appropriate scenarios for making managerial decisions and their prompt correction.

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Section: Related Workmentioning

confidence: 99%

Intellectual Scenario-synergetic Control of the Humidity and Temperature Regime of the Greenhouse Facilities

Polishchyk¹,

Lysenko²,

Osadchiy³

et al. 2022

IJC

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“…The model of DSIM in a synchronous frame (d,q) given in state-space form, is a fourthorder model (Khedher and Faouzi Mimouni, 2010;Kouki et al, 2013;Hossine and Katia, 2017) as:…”

Section: 6mentioning

confidence: 99%

“…As a result, the growing interest of the scientific and industrial communities in increasing the number of phases of electrical machines is beginning today. The most common example of the multiphase machines is the double star induction machine (double star induction motor [DSIM]), which offers a good technicaleconomic compromise (Khedher and Faouzi Mimouni, 2010;Kouki et al, 2013;Hossine and Katia, 2017).…”

Section: Introductionmentioning

confidence: 99%

Novel design of an optimized synergetic control for dual stator induction motor

Guermit

Kouzi

Bessedik

2019

COMPEL

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Purpose This paper aims to present a contribution to improve the performance of vector control scheme of double star induction motor drive (DSIM) by using an optimized synergetic control approach. The main advantage of synergetic control is that it supports all parametric and nonparametric uncertainties, which is not the case in several control strategies. Design/methodology/approach The suggested controller is developed based on the synergistic control theory and the particle swarm optimization (PSO) algorithm which allow to obtain the optimal parameter of suggested controller to improve the performance of control system. Findings To show the benefits of proposed controller, a comparative simulation results between conventional PI controller, sliding mode controller and suggested controller were carried out. Originality/value The obtained simulation results illustrate clearly that synergetic controller ensures a rapid response, asymptotic stability of the closed-loop system in the all range operating condition and system robustness in presence of parameter variation in all range of operating conditions.

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“…Synthesis of effective management strategies to control non-linear systems was examined by using the methods pacification [5], backstepping [6,7], robust [8,9] and synergistic control [5,10]. Among them, the most promising for complex greenhouse facilities are the methods of synergistic control, discussed in papers [10][11][12].…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Managing a greenhouse complex using the synergetic approach and neural networks

Dudnyk

Hachkovska

Zaiets

et al. 2019

EEJET

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Розглядається використання штучних нейронних мереж до синтезу iнтелектуальних систем з синергетичним законом керування. Показано, що досi всi об'єкти дослiдження, а вiдповiдно i закони керування, вважали лiнiйними, або намагались звести їх до таких, втрачаючи в певних особливостях. Проте, як свiдчить практика, реальнi об'єкти у своїй бiльшостi, є нелiнiйними. Розгляд таких об'єктiв iз спробою їх лiнеаризацiї призводить до того, що втрачаються важливi характеристики всього процесу. Основна частина тепличного комплексу складається саме iз нелiнiйних об'єктiв керування. Не винятком стала i теплиця та кожен технологiчний процес окремо. Запропоновано основнi положення синергетичного пiдходу до проблеми системного синтезу. Показано синергетичний синтез закону керування тепличним комплексом в умовах не контролюючих змiн технологiчних параметрiв та зовнiшнiх збурень. Використаний математичний апарат нечiткої логiки дає можливiсть реалiзацiї нечiткого керування. Особливо позитивно це проявляється за умов, коли процеси є складними для аналiзу на основi використання традицiйних кiлькiсних методiв. А також, коли iнформацiя, що поступає про об'єкт, неякiсна, неточна або невизначена. Саме така iнформацiя надходить для аналiзу та її подальшого використання, при вирощуваннi овочевої продукцiї у тепличних комплексах. Запропонований алгоритм синтезу нейромережевого регулятора для тепличного комплексу на основi заданого синергетичного закону керування. Алгоритм базується на поведiнцi синергетичного регулятора, що моделює значення температури та вологостi штучною нейронною мережею в результатi її навчання. Особливiсть запропонованого комплексного пiдходу до синтезу iнтелектуальної системи керування тепличним комплексом полягає в комбiнацiї принципу єдностi процесiв самоорганiзацiї та навчання нейронної мережi на попередньому етапi. Завдяки такому поєднанню, забезпечується подальше стiйке функцiонування системи iнтелектуального керування вирощування овочевої продукцiїКлючовi слова: синергетичний регулятор, нейронна мережа, iнтелектуальне керування, тепличний комплекс, овочева продукцiя

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Improvement of vector control of Dual Star Induction drive using synergetic approach

Cited by 6 publications

References 7 publications

Intellectual Scenario-synergetic Control of the Humidity and Temperature Regime of the Greenhouse Facilities

Intellectual Scenario-synergetic Control of the Humidity and Temperature Regime of the Greenhouse Facilities

Novel design of an optimized synergetic control for dual stator induction motor

Managing a greenhouse complex using the synergetic approach and neural networks

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