<scp>PSO</scp>
            based
            <scp>LQR‐PID</scp>
            output feedback for load frequency control of reduced power system model using balanced truncation

Pillai, Anju G.; Samuel, Elizabeth Rita

doi:10.1002/2050-7038.13012

Cited by 16 publications

(4 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The goal of the PSO algorithm is for a large number of particles to find an optimal solution in a multidimensional superbody. The multidimensional hyperbody, which can also be referred to as the multidimensional solution space, is the search space for the particle swarm to find the optimal problem [18]. It is assumed that in solving the optimization problem, the optimal solution obtained for each optimization problem is a particle in the search space, and all the particles are extended to the D-dimensional space.…”

Section: Particle Swarm Optimization (Pso) Algorithmmentioning

confidence: 99%

The Role of English Language and Literature in the Cultivation of Students’ Language Proficiency in the Context of Deep Learning

Jia

2023

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

In this paper, the PSO-LSTM algorithm is used to construct a model for evaluating students’ language proficiency, and the improvement of the acceleration factor and inertia weights is used to adjust the influence of the individual optimal position and the global optimal position in the speed update. For model performance judgment after optimization of LSTM hyperparameters, the PSO fitness function is replaced by MAPE and MSE functions. Finally, the student’s English composition texts were used as experimental parameters and input into the language proficiency evaluation model to verify the model performance and analyze the influence of English language literature on language proficiency. The results show that English language literature is effective in predicting 18.55% of the variance in English proficiency level for self-efficacy, 8.17% of the variance in English proficiency level for language attitude, and 0.47% of the variance in English proficiency level for learning anxiety, which indicates that English language literature has a significant effect on students’ English proficiency. This paper investigates the role mechanism of the English language and literature in the cultivation of student’s English proficiency, which provides a theoretical reference for the reform of English teaching in colleges and universities.

show abstract

Section: Particle Swarm Optimization (Pso) Algorithmmentioning

confidence: 99%

The Role of English Language and Literature in the Cultivation of Students’ Language Proficiency in the Context of Deep Learning

Jia

2023

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

show abstract

“…Arya reported a scaling factor-based fuzzy-PI (FPI) controller [19], fuzzy fractional-order integral derivative (FFOID) [20], and fuzzy-TIDF (FTIDN) controller [21], all tuned by the imperialist competitive algorithm (ICA) for traditional MAIPS. Pillai and Samuel [22] recently discussed designing the PSO-based LQR-PID approach for LFC using balanced truncation. In recent years, fractional-order (FO) controllers have been quite popular in control applications.…”

Section: Introductionmentioning

confidence: 99%

Fractional‐order PID and internal model control‐based dual‐loop load frequency control using teaching–learning optimization

Veerendar

Kumar

Sreeram

2023

Asian Journal of Control

View full text Add to dashboard Cite

A load frequency controller is essential to counter load disturbances and minimize unscheduled power flow between interlinked areas of a power system. Hence, this paper proposes a fractional-order proportional-integral derivative (FOPID)-based dual-loop control approach for load frequency control of multiarea nonreheated thermal power systems (NRTPS) using teaching-learning optimization (TLO). A stability equation-based predictive model is used with internal model control in the internal loop of the proposed approach, whereas the external loop contains TLO-based FOPID controller. The proposed method is tested on two-area and three-area NRTPSs under various operating conditions. It is validated from the simulation results that the proposed approach improves the system response substantially compared to the well-known existing techniques. The robustness of the proposed method is also demonstrated by performing sensitivity analysis with parametric uncertainties, random load disturbances, generation rate constraints, and governor dead zone.

show abstract

“…In [14][15][16][17][18], frequency restoration has been considered to control MGs. Te authors in [19][20][21][22][23][24][25][26] have employed meta-heuristic optimization-based algorithms such as the fuzzy, integration layered recurrent neural network methods, and cascade-based fractional order controllers to restore frequency deviation in multiarea systems based on hydrothermal power systems integrated with RESs.…”

Section: Introductionmentioning

confidence: 99%

Robust Frequency Control of Microgrids: A Mixed $H_{2} / Maleki 1, Nikoukar 2, Tousifian 3 2023 International Transactions on Electrical Energy Systems5000View full text Add to dashboard CiteThis article proposes a robust inertial controller for converter-based distributed generators employed in low-inertia power systems like microgrids. The increasing penetration level of renewable energy sources based on power electronics converters in modern power systems reduces the inertial features of the system. It also increases concerns associated with the system uncertainty and sensitivity against disturbances. To cope with these challenges, by employing the proposed linear matrix inequality (LMI)-based mixed

H

2

/

H

∞

robust method, an optimal robust controller aided for inertial support as well as fast frequency restoration is provided. Using the proposed solution not only presents a better inertial response but also proposes a faster frequency restoration, by which the system’s frequency can be restored immediately following any disturbance, even in the presence of system uncertainties. Through in-detailed frequency response analysis and time-domain simulations for different scenarios, it is illustrated that the proposed mechanism can be successfully employed to address the inertial requirements in power electronic-based power systems. In addition, the proposed LMI-based mixed

H

2

/

H

∞

control solution is compared with a number of other solutions to illustrate its better performance against disturbances. Simulation results validate the merits and effectiveness of the proposed controller.show abstractscite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health. Contact Info customersupport@researchsolutions.com 10624 S. Eastern Ave., Ste. A-614 Henderson, NV 89052, USA Product Browser Extension Assistant by scite Citation Statement Search Reference Check Visualizations Dashboards Explore Journals Explore Organizations Explore Funders Embedding Badge Embedding Citation Search Pricing Resources Blog Help & FAQ Accessibility Statement API Terms For Universities & Governments For Researchers For Publishers For Corporate, Pharma & Enterprise Author Marketing Become an Affiliate Get an organization trial or quote scite Data & Services About News & Press Careers Read our Paper Coverage This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply. Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information Copyright © 2024 scite LLC. All rights reserved. Made with 💙 for researchers Part of the Research Solutions Family.window.__SCITE_STORE_STATE = {"addReportDashboardModal":{"selectedPapers":[]},"ui":{"referralPartner":null,"freeReports":0,"bannerContent":null,"bannerClosed":false,"navMenu":{},"createDashboardFromSearchResultsModalShow":false,"savedSearchModalShow":false,"searchFilterModalShow":false,"flagModalShow":false,"resetPasswordModalShow":false,"loginModalShow":false,"referenceCheckModalShow":false,"deleteDashboardModalShow":false,"addReportToDashboardModalShow":false,"shareDashboardModalShow":false,"editDashboardModalShow":false,"upgradeModalShow":false,"exportReportModalShow":false,"exportReferenceModalShow":false,"generateCitationModalShow":false,"exportDashboardModalShow":false,"dashboardLimitErrorModalShow":false,"whatIsThisReportModalShow":false,"whatIsThisSearchModalShow":false,"whatIsAssistantModalShow":false,"trialOverModalShow":false,"activateTrialModalShow":false,"cancelTrialCheckoutModalShow":false,"cookieModalShow":false,"personaModalShow":false,"loggedOutModalShow":true,"modalFromContext":"","shownModals":[],"hasUser":false,"user":null,"ipLocationData":{"data":null,"error":false,"loading":false},"fetchingUser":false,"savingUser":false,"saveUserError":false,"onboardingLoadTracker":{"state":undefined},"userEntitlements":null,"entitlementsLoading":false,"referralsLoading":false,"pageError":null,"browser":null,"extensionLoaded":false,"organizationLicense":{"hasLicense":false},"linkResolver":null,"sickoMode":false,"authors":[],"navOpen":false,"showMobileSearch":false,"redeemCodeLoading":false,"redeemCodeError":null,"redeemCodeSuccess":false,"applyDiscountLoading":false,"applyDiscountError":null,"applyDiscountSuccess":false,"userDiscount":null,"search":{"term":"","focused":false,"autocompletesLoadTracker":{},"autocompletes":{}},"referencesToExport":[],"citeGeneratorPaperData":{},"dimensions":{},"cookiePreference":null,"userChurnKey":null,"churnKeyLoading":false,"fullTextLinkState":{},"agAvailabilityState":{},"agAvailabilityQueue":[]},"verifyEmail":{"loading":false,"verified":false,"expired":false},"dashboard":{"id":"","name":"","displayName":"","normalizedName":"","description":"","slug":"","dashboardType":"","accessType":"","isPublic":null,"componentLayout":[],"doiQuery":{},"journalMetadata":{},"affiliationMetadata":{},"institutionMetadata":{},"haveAccessToDashboard":null,"lastUpdated":null,"doisUpdatedTS":null,"doisRefreshedTS":null,"refreshStatus":"","loadState":{},"deleteDashboardError":false,"deletingDashboard":false,"totalDoiCount":0,"matchedDoiCount":0,"unmatchedDoiCount":0,"exportLoadTracker":{},"setDashboardUsersLoading":false,"setDashboardUsersError":false,"setDashboardUsersSuccess":false,"dashboardAccessList":null,"getDashboardAccessListLoading":false,"getDashboardAccessListSuccess":false,"getDashboardAccessListError":false},"notifications":{"notifications":[],"loading":false,"error":null,"notificationItems":[],"notificationItemsLoading":false,"notificationItemsError":null,"notificationItemsPage":1,"notificationItemsTotal":0,"newNotificationItems":0,"notificationItemsFilters":{},"dropDownNotificationItems":[],"dropDownNotificationItemsLoading":false,"dropDownNotificationItemsError":null,"notificationSetStatusLoading":false,"notificationSetStatusError":null},"report":{"paper":"10.1002\u002F2050-7038.13012","tally":"10.1002\u002F2050-7038.13012","citations":[{"id":3528196093,"source":"10.2478\u002Famns.2023.2.01343","target":"10.1002\u002F2050-7038.13012","negative":0.010508881509304046,"positive":0.006056481506675482,"neutral":1,"section":"particle swarm optimization (pso) algorithm","type":"mentioning","typeConfidence":1,"snippet":"The goal of the PSO algorithm is for a large number of particles to find an optimal solution in a multidimensional superbody. The multidimensional hyperbody, which can also be referred to as the multidimensional solution space, is the search space for the particle swarm to find the optimal problem \u003Ccite data-doi=\"10.1002\u002F2050-7038.13012\"\u003E[18]\u003C\u002Fcite\u003E. It is assumed that in solving the optimization problem, the optimal solution obtained for each optimization problem is a particle in the search space, and all the particles are extended to the D-dimensional space.","lang":"en","langConfidence":"0.9100000262260437","refLocation":"b17\u002F1","memberId":374,"selfCites":[],"snippetHidden":false},{"id":3257419811,"source":"10.1002\u002Fasjc.3022","target":"10.1002\u002F2050-7038.13012","negative":0.005047024413943291,"positive":0.010452193208038807,"neutral":1,"section":"introduction","type":"mentioning","typeConfidence":1,"snippet":"Arya reported a scaling factor-based fuzzy-PI (FPI) controller \u003Ccite data-doi=\"10.1016\u002Fj.jfranklin.2018.02.004\"\u003E[19]\u003C\u002Fcite\u003E, fuzzy fractional-order integral derivative (FFOID) \u003Ccite data-doi=\"10.1002\u002Fer.4767\"\u003E[20]\u003C\u002Fcite\u003E, and fuzzy-TIDF (FTIDN) controller \u003Ccite data-doi=\"10.1016\u002Fj.renene.2019.02.038\"\u003E[21]\u003C\u002Fcite\u003E, all tuned by the imperialist competitive algorithm (ICA) for traditional MAIPS. Pillai and Samuel \u003Ccite data-doi=\"10.1002\u002F2050-7038.13012\"\u003E[22]\u003C\u002Fcite\u003E recently discussed designing the PSO-based LQR-PID approach for LFC using balanced truncation. In recent years, fractional-order (FO) controllers have been quite popular in control applications.","lang":"en","langConfidence":"0.8999999761581421","refLocation":"b21\u002F1","memberId":311,"selfCites":[],"snippetHidden":false},{"id":3205897701,"source":"10.1155\u002F2023\u002F6872765","target":"10.1002\u002F2050-7038.13012","negative":0.0043125696480274195,"positive":0.0032297575380653143,"neutral":1,"section":"introduction","type":"mentioning","typeConfidence":1,"snippet":"In \u003Ccite data-doi=\"10.1002\u002F2050-7038.13012\"\u003E[14]\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.1016\u002Fj.apenergy.2020.114978\"\u003E[15]\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.20508\u002Fijrer.v9i2.9222.g7637\"\u003E[16]\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.1109\u002Faccess.2018.2826015\"\u003E[17]\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.1109\u002Faccess.2020.2987387\"\u003E[18]\u003C\u002Fcite\u003E, frequency restoration has been considered to control MGs. Te authors in \u003Ccite data-doi=\"10.1002\u002Fer.6328\"\u003E[19]\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.1049\u002Fiet-gtd.2019.0935\"\u003E[20]\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.1049\u002Frpg2.12061\"\u003E[21]\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.1109\u002Fsgc.2017.8308864\"\u003E[22]\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.1063\u002F1.5018338\"\u003E[23]\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.7305\u002Fautomatika.2017.12.1707\"\u003E[24]\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.1016\u002Fj.jestch.2020.08.015\"\u003E[25]\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.1080\u002F15325008.2020.1793829\"\u003E[26]\u003C\u002Fcite\u003E have employed meta-heuristic optimization-based algorithms such as the fuzzy, integration layered recurrent neural network methods, and cascade-based fractional order controllers to restore frequency deviation in multiarea systems based on hydrothermal power systems integrated with RESs.","lang":"en","langConfidence":"0.9100000262260437","refLocation":"b13\u002F1","memberId":98,"selfCites":[],"snippetHidden":false},{"id":2969843293,"source":"10.1155\u002F2022\u002F6286500","target":"10.1002\u002F2050-7038.13012","negative":0.012645578384399414,"positive":0.014112712815403938,"neutral":1,"section":"introduction","type":"mentioning","typeConfidence":1,"snippet":"According to a study of the existing literature, the performance of conventional controllers in frequency regulation of power systems with\u002Fwithout RERs incorporated has been widely used \u003Ccite data-doi=\"10.1016\u002Fj.rser.2012.02.009\"\u003E[2,\u003C\u002Fcite\u003E\u003Ccite data-doi=\"10.1016\u002Fj.ijepes.2018.11.005\"\u003E3]\u003C\u002Fcite\u003E. An output feedback-based optimal control for in frequency regulation of reduced power systems model has been discussed in reference \u003Ccite data-doi=\"10.1002\u002F2050-7038.13012\"\u003E[13]\u003C\u002Fcite\u003E. In the above-cited works, traditional controllers considerably improve system dynamics.","lang":"en","langConfidence":"0.9399999976158142","refLocation":"b12\u002F1","memberId":98,"selfCites":[],"snippetHidden":false},{"source":"10.1007\u002Fs11831-023-10060-9","target":"10.1002\u002F2050-7038.13012","selfCites":[],"dataSource":"CR"},{"source":"10.1007\u002Fs40435-022-01082-5","target":"10.1002\u002F2050-7038.13012","selfCites":[],"dataSource":"CR"},{"source":"10.1016\u002Fj.prime.2023.100135","target":"10.1002\u002F2050-7038.13012","selfCites":[],"dataSource":"CR"},{"source":"10.1109\u002Fceect59667.2023.10420716","target":"10.1002\u002F2050-7038.13012","selfCites":[],"dataSource":"CR"}],"citationTallies":{"10.1002\u002Fasjc.3022":{"total":2,"supporting":0,"contradicting":0,"mentioning":2,"unclassified":0,"doi":"10.1002\u002Fasjc.3022","citingPublications":6},"10.1155\u002F2022\u002F6286500":{"total":2,"supporting":0,"contradicting":0,"mentioning":2,"unclassified":0,"doi":"10.1155\u002F2022\u002F6286500","citingPublications":3},"10.1155\u002F2023\u002F6872765":{"total":0,"supporting":0,"contradicting":0,"mentioning":0,"unclassified":0,"doi":"10.1155\u002F2023\u002F6872765","citingPublications":5},"10.2478\u002Famns.2023.2.01343":{"total":0,"supporting":0,"contradicting":0,"mentioning":0,"unclassified":0,"doi":"10.2478\u002Famns.2023.2.01343","citingPublications":0},"10.1007\u002Fs11831-023-10060-9":{"total":0,"supporting":0,"contradicting":0,"mentioning":0,"unclassified":0,"doi":"10.1007\u002Fs11831-023-10060-9","citingPublications":1},"10.1007\u002Fs40435-022-01082-5":{"total":0,"supporting":0,"contradicting":0,"mentioning":0,"unclassified":0,"doi":"10.1007\u002Fs40435-022-01082-5","citingPublications":2},"10.1016\u002Fj.prime.2023.100135":{"total":2,"supporting":0,"contradicting":0,"mentioning":2,"unclassified":0,"doi":"10.1016\u002Fj.prime.2023.100135","citingPublications":8},"10.1109\u002Fceect59667.2023.10420716":{"total":0,"supporting":0,"contradicting":0,"mentioning":0,"unclassified":0,"doi":"10.1109\u002Fceect59667.2023.10420716","citingPublications":0}},"metadata":{"totalCitationCount":4,"restrictedCitationCount":5,"distinctSourceCount":16},"papers":{"10.1155\u002F2022\u002F6286500":{"id":11577406220,"doi":"10.1155\u002F2022\u002F6286500","slug":"frequency-regulation-of-nonlinear-power-y8bpy0pr","type":"journal-article","title":"Frequency Regulation of Nonlinear Power Systems using Neural Network Observer-Based Optimized Resilient Controller","abstract":"This study introduces a resilient frequency controller for nonlinear interconnected power systems to counteract endogenous\u002Fexogenous system disturbances. A neural network-based observer (NNO) is intended to estimate lumped system disturbances, such as unmodelled dynamics and unknown disturbances. The estimated NNO’s output is incorporated with a second-order sliding mode controller (SOSMC) to minimize chattering in the control effort and improve the nominal performance of the undertaken plant. The design parameters of SOSMC have been optimally identified by applying Harris hawk optimization (HHO), exercising integral error-based objective function. HHO has demonstrated superior tuning capabilities than other well-known optimization methodologies in terms of convergence rate and transient measurements of system outputs. The asymptotic convergence of estimated error and overall stability of the system has been established employing the Lyapunov argument. System outputs are compared with the results reported in the literature to validate the efficacy of the proposed resilient frequency controller. Presented results showcase the mastery of the applied NNO-based SOSMC over its counterparts in weaker chattering, fast disturbance rejection, and a high degree of robustness against endogenous\u002Fexogenous disturbances.","authors":[{"family":"Patel","given":"Vivek Kumar","affiliation":"Motilal Nehru National Institute of Technology","authorSlug":"vivek-kumar-patel-lX541v","authorName":"Vivek Kumar Patel","authorID":"10046736","authorLastKnownAffiliationId":8404,"authorSequenceNumber":1,"affiliationSlug":"motilal-nehru-national-institute-of-Wn4Q","affiliationID":"8404"},{"family":"Guha","given":"Dipayan","affiliation":"Motilal Nehru National Institute of Technology","authorSlug":"dipayan-guha-W8PnE5","authorName":"Dipayan Guha","authorID":"6907892","authorLastKnownAffiliationId":8404,"authorSequenceNumber":2,"affiliationSlug":"motilal-nehru-national-institute-of-Wn4Q","affiliationID":"8404"},{"family":"Purwar","given":"Shubhi","affiliation":"Motilal Nehru National Institute of Technology","authorSlug":"shubhi-purwar-MVdxQp","authorName":"Shubhi Purwar","authorID":"7237196","authorLastKnownAffiliationId":8404,"authorSequenceNumber":3,"affiliationSlug":"motilal-nehru-national-institute-of-Wn4Q","affiliationID":"8404"}],"keywords":[],"year":2022,"shortJournal":"International Transactions on Electrical Energy Systems","publisher":"Hindawi Limited","volume":"2022","page":"1-21","memberId":98,"issns":["2050-7038"],"editorialNotices":[],"journalSlug":"international-transactions-on-electrical-energy-J1XpY","journal":"International Transactions on Electrical Energy Systems","preprintLinks":[],"publicationLinks":[],"normalizedTypes":["article"]},"10.1155\u002F2023\u002F6872765":{"id":11644231926,"doi":"10.1155\u002F2023\u002F6872765","slug":"robust-frequency-control-of-microgrids-RV996594","type":"journal-article","title":"Robust Frequency Control of Microgrids: A Mixed \u003Cmath xmlns=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"M1\"\u003E\n \u003Cmsub\u003E\n \u003Cmrow\u003E\n \u003Cmi mathvariant=\"script\"\u003EH\u003C\u002Fmi\u003E\n \u003C\u002Fmrow\u003E\n \u003Cmrow\u003E\n \u003Cmn\u003E2\u003C\u002Fmn\u003E\n \u003C\u002Fmrow\u003E\n \u003C\u002Fmsub\u003E\n \u003Cmo\u003E\u002F\u003C\u002Fmo\u003E\n \u003Cmsub\u003E\n \u003Cmrow\u003E\n \u003Cmi mat","abstract":"This article proposes a robust inertial controller for converter-based distributed generators employed in low-inertia power systems like microgrids. The increasing penetration level of renewable energy sources based on power electronics converters in modern power systems reduces the inertial features of the system. It also increases concerns associated with the system uncertainty and sensitivity against disturbances. To cope with these challenges, by employing the proposed linear matrix inequality (LMI)-based mixed \n \n \n \n H\n \n \n 2\n \n \n \u002F\n \n \n H\n \n \n ∞\n \n \n \n robust method, an optimal robust controller aided for inertial support as well as fast frequency restoration is provided. Using the proposed solution not only presents a better inertial response but also proposes a faster frequency restoration, by which the system’s frequency can be restored immediately following any disturbance, even in the presence of system uncertainties. Through in-detailed frequency response analysis and time-domain simulations for different scenarios, it is illustrated that the proposed mechanism can be successfully employed to address the inertial requirements in power electronic-based power systems. In addition, the proposed LMI-based mixed \n \n \n \n H\n \n \n 2\n \n \n \u002F\n \n \n H\n \n \n ∞\n \n \n \n control solution is compared with a number of other solutions to illustrate its better performance against disturbances. Simulation results validate the merits and effectiveness of the proposed controller.","authors":[{"family":"Maleki","given":"Shahryar","affiliation":"Islamic Azad University Saveh","authorSlug":"shahryar-maleki-mAQrvr","authorName":"Shahryar Maleki","authorID":"24244643","authorLastKnownAffiliationId":214220,"authorSequenceNumber":1,"affiliationSlug":"islamic-azad-university-saveh-yZjrr","affiliationID":"214220"},{"family":"Nikoukar","given":"Javad","affiliation":"Islamic Azad University Saveh","authorSlug":"javad-nikoukar-4lVNaV","authorName":"Javad Nikoukar","authorID":"25119542","authorLastKnownAffiliationId":214220,"authorSequenceNumber":2,"affiliationSlug":"islamic-azad-university-saveh-yZjrr","affiliationID":"214220"},{"family":"Tousifian","given":"Mohammad Hassan","affiliation":"Islamic Azad University Saveh","authorSlug":"mohammad-hassan-tousifian-kbpxjg","authorName":"Mohammad Hassan Tousifian","authorID":"35750768","authorLastKnownAffiliationId":214220,"authorSequenceNumber":3,"affiliationSlug":"islamic-azad-university-saveh-yZjrr","affiliationID":"214220"}],"keywords":[],"year":2023,"shortJournal":"International Transactions on Electrical Energy Systems","publisher":"Hindawi Limited","volume":"2023","page":"1-14","memberId":98,"issns":["2050-7038"],"editorialNotices":[],"journalSlug":"international-transactions-on-electrical-energy-J1XpY","journal":"International Transactions on Electrical Energy Systems","preprintLinks":[],"publicationLinks":[],"normalizedTypes":["article"]},"10.1002\u002Fasjc.3022":{"id":11625443220,"doi":"10.1002\u002Fasjc.3022","slug":"fractional-order-pid-and-internal-model-y8bmzmzr","type":"journal-article","title":"Fractional‐order PID and internal model control‐based dual‐loop load frequency control using teaching–learning optimization","abstract":"A load frequency controller is essential to counter load disturbances and minimize unscheduled power flow between interlinked areas of a power system. Hence, this paper proposes a fractional-order proportional-integral derivative (FOPID)-based dual-loop control approach for load frequency control of multiarea nonreheated thermal power systems (NRTPS) using teaching-learning optimization (TLO). A stability equation-based predictive model is used with internal model control in the internal loop of the proposed approach, whereas the external loop contains TLO-based FOPID controller. The proposed method is tested on two-area and three-area NRTPSs under various operating conditions. It is validated from the simulation results that the proposed approach improves the system response substantially compared to the well-known existing techniques. The robustness of the proposed method is also demonstrated by performing sensitivity analysis with parametric uncertainties, random load disturbances, generation rate constraints, and governor dead zone.","authors":[{"family":"Veerendar","given":"Tejavath","affiliation":"Motilal Nehru National Institute of Technology","authorSlug":"tejavath-veerendar-G6z3P1","authorName":"Tejavath Veerendar","authorID":"18742613","authorLastKnownAffiliationId":8404,"authorSequenceNumber":1,"affiliationSlug":"motilal-nehru-national-institute-of-Wn4Q","affiliationID":"8404"},{"family":"Kumar","given":"Deepak","affiliation":"Motilal Nehru National Institute of Technology","authorSlug":"deepak-kumar-6M9nxk","authorName":"Deepak Kumar","authorID":"8355754","authorLastKnownAffiliationId":8404,"authorSequenceNumber":2,"affiliationSlug":"motilal-nehru-national-institute-of-Wn4Q","affiliationID":"8404"},{"family":"Sreeram","given":"Victor","affiliation":"University of Western Australia","authorSlug":"victor-sreeram-pnp6lx","authorName":"Victor Sreeram","authorID":"5605030","authorLastKnownAffiliationId":24779,"authorSequenceNumber":3,"affiliationSlug":"university-of-western-australia-K3Mp","affiliationID":"24779"}],"keywords":["controller design","load frequency control","model reduction","teaching-learning optimization"],"year":2023,"shortJournal":"Asian Journal of Control","publisher":"Wiley","issue":"4","volume":"25","page":"2482-2497","memberId":311,"issns":["1561-8625","1934-6093"],"editorialNotices":[],"journalSlug":"asian-journal-of-control-keKl5","journal":"Asian Journal of Control","preprintLinks":[],"publicationLinks":[],"normalizedTypes":["article"]},"10.2478\u002Famns.2023.2.01343":{"id":12023434341,"doi":"10.2478\u002Famns.2023.2.01343","slug":"the-role-of-english-language-XxmV5LLk","type":"journal-article","title":"The Role of English Language and Literature in the Cultivation of Students’ Language Proficiency in the Context of Deep Learning","abstract":"In this paper, the PSO-LSTM algorithm is used to construct a model for evaluating students’ language proficiency, and the improvement of the acceleration factor and inertia weights is used to adjust the influence of the individual optimal position and the global optimal position in the speed update. For model performance judgment after optimization of LSTM hyperparameters, the PSO fitness function is replaced by MAPE and MSE functions. Finally, the student’s English composition texts were used as experimental parameters and input into the language proficiency evaluation model to verify the model performance and analyze the influence of English language literature on language proficiency. The results show that English language literature is effective in predicting 18.55% of the variance in English proficiency level for self-efficacy, 8.17% of the variance in English proficiency level for language attitude, and 0.47% of the variance in English proficiency level for learning anxiety, which indicates that English language literature has a significant effect on students’ English proficiency. This paper investigates the role mechanism of the English language and literature in the cultivation of student’s English proficiency, which provides a theoretical reference for the reform of English teaching in colleges and universities.","authors":[{"family":"Jia","given":"Manli","affiliation":"School of Foreign Languages , Huanghuai University , Zhumadian , Henan , , China ."}],"keywords":["PSO-LSTM algorithm","Speedup factor","Global optimum","English language and literature","Hyperparameter optimization AMS 2010 codes: 03B65"],"year":2023,"publisher":"Walter de Gruyter GmbH","issue":"1","volume":"9","memberId":374,"issns":["2444-8656"],"editorialNotices":[],"journalSlug":"applied-mathematics-and-nonlinear-sciences-b2gJ1","journal":"Applied Mathematics and Nonlinear Sciences","preprintLinks":[],"publicationLinks":[],"normalizedTypes":["article"]},"10.1007\u002Fs11831-023-10060-9":{"id":12079282121,"doi":"10.1007\u002Fs11831-023-10060-9","slug":"comprehensive-review-of-metaheuristic-algorithms-8G9W0Wwm","type":"journal-article","title":"Comprehensive Review of Metaheuristic Algorithms (MAs) for Optimal Control (OCl) Improvement","authors":[{"family":"Mohammed","given":"Usman","orcid":"0000-0002-7420-8088"},{"family":"Karataev","given":"Tologon"},{"family":"Oshiga","given":"Omotayo"},{"family":"Oghenewvogaga","given":"Oghorada"}],"year":2024,"shortJournal":"Arch Computat Methods Eng","publisher":"Springer Science and Business Media LLC","issue":"5","volume":"31","page":"2785-2903","memberId":297,"issns":["1134-3060","1886-1784"],"editorialNotices":[],"journalSlug":"archives-of-computational-methods-in-PQ4LL","journal":"Archives of Computational Methods in Engineering","preprintLinks":[],"publicationLinks":[],"normalizedTypes":["article"]},"10.1007\u002Fs40435-022-01082-5":{"id":11607880358,"doi":"10.1007\u002Fs40435-022-01082-5","slug":"robust-lqr-control-based-on-gZJVb8zd","type":"journal-article","title":"Robust LQR control based on multidimensional particle swarm optimization for enhancing the dynamic performance of poultry house system","authors":[{"family":"Lahlouh","given":"Ilyas","affiliation":"Mohammed V University","authorSlug":"ilyas-lahlouh-Ma5GE9","authorName":"Ilyas Lahlouh","authorID":"14937308","authorLastKnownAffiliationId":13612,"authorSequenceNumber":1,"affiliationSlug":"mohammed-v-university-01Ge","affiliationID":"13612"},{"family":"Rerhrhaye","given":"Fathallah","affiliation":"Mohammed V University","authorSlug":"fathallah-rerhrhaye-RZ4y4G","authorName":"Fathallah Rerhrhaye","authorID":"17593770","authorLastKnownAffiliationId":13612,"authorSequenceNumber":2,"affiliationSlug":"mohammed-v-university-01Ge","affiliationID":"13612"},{"family":"Elakkary","given":"Ahmed","affiliation":"Mohammed V University","authorSlug":"ahmed-elakkary-PDPMgb","authorName":"Ahmed Elakkary","authorID":"14030601","authorLastKnownAffiliationId":13612,"authorSequenceNumber":3,"affiliationSlug":"mohammed-v-university-01Ge","affiliationID":"13612"},{"family":"Sefiani","given":"Nacer","affiliation":"Mohammed V University","authorSlug":"nacer-sefiani-YD6KQz","authorName":"Nacer Sefiani","authorID":"13984651","authorLastKnownAffiliationId":13612,"authorSequenceNumber":4,"affiliationSlug":"mohammed-v-university-01Ge","affiliationID":"13612"},{"family":"Bybi","given":"Abdelmajid","affiliation":"Mohammed V University","authorSlug":"abdelmajid-bybi-xQK9jD","authorName":"Abdelmajid Bybi","authorID":"9404466","authorLastKnownAffiliationId":13612,"authorSequenceNumber":5,"affiliationSlug":"mohammed-v-university-01Ge","affiliationID":"13612"}],"year":2022,"shortJournal":"Int. J. Dynam. Control","publisher":"Springer Science and Business Media LLC","issue":"4","volume":"11","page":"1593-1608","memberId":297,"issns":["2195-268X","2195-2698"],"editorialNotices":[],"journalSlug":"international-journal-of-dynamics-and-y8b0R","journal":"International Journal of Dynamics and Control","preprintLinks":[],"publicationLinks":[],"normalizedTypes":["article"]},"10.1016\u002Fj.prime.2023.100135":{"id":11632436000,"doi":"10.1016\u002Fj.prime.2023.100135","slug":"optimal-design-of-pi-pd-dual-3nw0bEpd","type":"journal-article","title":"Optimal design of PI\u002FPD dual mode controller based on quasi opposition based learning for power system frequency control","authors":[{"family":"Tripathy","given":"Sabita","authorSlug":"sabita-tripathy-D1Zzvw","authorName":"Sabita Tripathy","authorID":"4049963","authorLastKnownAffiliationId":24782,"authorSequenceNumber":1},{"family":"Debnath","given":"Manoj Kumar","authorSlug":"manoj-kumar-debnath-38KGRK","authorName":"Manoj Kumar Debnath","authorID":"7875388","authorLastKnownAffiliationId":24782,"authorSequenceNumber":2},{"family":"Kar","given":"Sanjeeb Kumar","authorSlug":"sanjeeb-kumar-kar-d33JmG","authorName":"Sanjeeb Kumar Kar","authorID":"7698918","authorLastKnownAffiliationId":24782,"authorSequenceNumber":3}],"year":2023,"shortJournal":"e-Prime - Advances in Electrical Engineering, Electronics and E","publisher":"Elsevier BV","volume":"4","page":"100135","memberId":78,"issns":["2772-6711"],"editorialNotices":[],"journalSlug":"e-prime-advances-in-electrical-M295m","journal":"E-Prime - Advances in Electrical Engineering, Electronics and Energy","preprintLinks":[],"publicationLinks":[],"normalizedTypes":["article"]},"10.1109\u002Fceect59667.2023.10420716":{"id":12093741219,"doi":"10.1109\u002Fceect59667.2023.10420716","slug":"nonlinear-modeling-and-control-of-D1gQwY2Y","type":"proceedings-article","title":"Nonlinear Modeling and Control of a Hydropower Plant: A Comparative Study of Classical and LQR-Based Governors","authors":[{"family":"Viscarra-Gallardo","given":"Victor","affiliation":"Northeastern University,Electrical and Computer Engineering Department,Boston,MA,USA"},{"family":"Corrales-Arcienega","given":"Rodrigo","affiliation":"ENDE Guaracachi S.A.,Santa Cruz,Bolivia"},{"family":"Triveno-Vargas","given":"Francisco J.","affiliation":"UNIARA,Engineering Department,Sao Paolo,Brazil"}],"year":2023,"publisher":"IEEE","page":"155-162","memberId":263,"issns":[],"editorialNotices":[],"journal":"2023 5th International Conference on Electrical Engineering and Control Technologies (CEECT)","preprintLinks":[],"publicationLinks":[],"normalizedTypes":["other"]},"10.1002\u002F2050-7038.13012":{"id":11135935614,"doi":"10.1002\u002F2050-7038.13012","slug":"scp-pso-scp-based-scp-lqr-pid-scp-output-feedback-gZppNbE5","type":"journal-article","title":"\u003Cscp\u003EPSO\u003C\u002Fscp\u003E\n based\n \u003Cscp\u003ELQR‐PID\u003C\u002Fscp\u003E\n output feedback for load frequency control of reduced power system model using balanced truncation","abstract":"Hydro power plants are in general more stable to the load demands and thus the change in frequency can be easily controlled. Whereas in multi-source interconnected power system the stability of the system is marginal. In certain conditions the system is also unmeasurable to implement the load frequency control. Linear Quadratic Regulator with output feedback design forms a familiar optimal choice to tackle this problem, but the technique is dependent on the choice of the weighting matrices Q and R for the performance index.Particle swarm optimization technique is commonly used in power system applications for obtaining the weighting matrices. In this paper, an output feedback-based LQR-PID technique is used to obtain an improved response for the multisource systems. Due to integral action, the steady-state value achieved for the change in frequency is minimized. In addition, if the system is unmeasurable LQR technique cannot be applied, in the literature, Linear Quadratic Gaussian is used for the same. Here a balanced truncation model order reduction is used on the original system to convert it to a measurable system.In addition, a comparative analysis is included to highlight the efficacy of the proposed control technique.","authors":[{"family":"Pillai","given":"Anju G.","affiliation":"A P J Abdul Kalam Technological University","authorSlug":"anju-g-pillai-5KPwQR","authorName":"Anju G. Pillai","authorID":"15918369","authorLastKnownAffiliationId":10105,"authorSequenceNumber":1,"affiliationSlug":"a-p-j-abdul-kalam-AOZe","affiliationID":"10105"},{"family":"Samuel","given":"Elizabeth Rita","affiliation":"A P J Abdul Kalam Technological University","authorSlug":"elizabeth-rita-samuel-b80W6v","authorName":"Elizabeth Rita Samuel","authorID":"14425659","authorLastKnownAffiliationId":219394,"authorSequenceNumber":2,"affiliationSlug":"a-p-j-abdul-kalam-AOZe","affiliationID":"10105"}],"keywords":["balanced truncation","linear quadratic regulator","load frequency control","model order reduction","particle swarm optimization"],"year":2021,"shortJournal":"Int Trans Electr Energ Syst","publisher":"Hindawi Limited","issue":"9","volume":"31","memberId":98,"issns":["2050-7038","2050-7038"],"editorialNotices":[],"journalSlug":"international-transactions-on-electrical-energy-J1XpY","journal":"International Transactions on Electrical Energy Systems","preprintLinks":[],"publicationLinks":[],"normalizedTypes":["article"]}},"tallies":{"10.1002\u002F2050-7038.13012":{"total":4,"supporting":0,"contradicting":0,"mentioning":4,"unclassified":0,"doi":"10.1002\u002F2050-7038.13012","citingPublications":16}},"selectCitation":null,"references":[],"referencesTotalCount":31,"referencePapers":{},"referenceTallies":{},"referencesByPapers":[],"paperLoadTracker":{"state":"loaded","key":"scp-pso-scp-based-scp-lqr-pid-scp-output-feedback-gZppNbE5"},"citingCountsLoadTracker":{"state":"loading"},"citationsLoadTracker":{"state":"loaded"},"referencesLoadTracker":{"state":"loaded"},"claimPaperLoadTracker":{},"flagCitationLoadTracker":{},"filters":{"showMobile":false,"sort":{"id":"relevancy","value":null,"label":"Relevance"},"supporting":null,"mentioning":null,"contradicting":null,"unclassified":null,"selfCite":null,"independent":null,"publishedRange":null,"citationsPerPage":10,"currentPage":1,"textMatch":"","citationIDs":[],"sourceDOIIDs":[],"withCitationStatements":true,"withoutCitationStatements":true,"journals":[],"authors":[],"pubtypes":[],"sections":[],"showReferences":false},"flag":{"citation":null,"citationType":null,"type":"","comment":""},"moreLikeThisResults":null,"moreLikeThisLoading":false,"exportReportLoading":false},"loginModal":{"mode":"login","name":{"placeholder":"Full Name","type":"text","value":""},"email":{"type":"email","placeholder":"Email","value":""},"password":{"type":"password","placeholder":"Password","value":""},"repeatPassword":{"type":"password","placeholder":"Repeat Password","value":""},"privacyAgreed":false,"loading":false,"userSignupType":null,"userSignupTypeLoading":false,"userSignupTypeEmail":null,"userSignupTypeOrg":null,"userSignupTypeEmailDomains":null,"fetchedSignupType":false,"fetchedSignupTypeError":false}}[]{"namedChunks":[]}(function(i,s,o,g,r,a,m){i[o]=i[o]||function(){(i[o].q=i[o].q||[]).push(arguments)};
a=s.createElement(g);m=s.getElementsByTagName(g)[0];a.async=1;a.src=r+'?auth='+
s.getElementById(o+'-js').getAttribute('data-pw-auth');m.parentNode.insertBefore(a,m);
})(window,document,'profitwell','script','https://public.profitwell.com/js/profitwell.js'); window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag("consent", "default", {ad_storage: "denied", analytics_storage: "denied", wait_for_update: 1500}); gtag('js', new Date()); gtag('config', 'AW-614125746'); (function(t,a,p){t.TapfiliateObject=a;t[a]=t[a]||function(){ (t[a].q=t[a].q||[]).push(arguments)}})(window,'tap');

tap('create', '48731-1a14bc', { integration: "javascript" });
tap('detect'); window.__MathJax_State = {
isReady: false,
promise: new Promise(resolve => {
window.MathJax = {
// MathJax can be configured as desired in addition to these options.
startup: {
ready: () => {
// Do whatever MathJax would normally do at this point.
MathJax.startup.defaultReady();
// Set the flag and resolve the promise.
window.MathJax_State__.isReady = true;
resolve();
}
},
tex: {
inlineMath: [
["$", "$"],
],
},
svg: {
fontCache: "global"
}
};
})
}; var _rollbarConfig = {
accessToken: "2c3f1a7fb80c4667a8370b6d5e60b850",
captureUncaught: true,
captureUnhandledRejections: true,
payload: {
environment: "staging",
client: {
javascript: {
code_version: "null"
}
}
}
};
// Rollbar Snippet
!function(r){function e(n){if(o[n])return o[n].exports;var t=o[n]={exports:{},id:n,loaded:!1};return r[n].call(t.exports,t,t.exports,e),t.loaded=!0,t.exports}var o={};return e.m=r,e.c=o,e.p="",e(0)}([function(r,e,o){"use strict";var n=o(1),t=o(4);_rollbarConfig=_rollbarConfig||{},_rollbarConfig.rollbarJsUrl=_rollbarConfig.rollbarJsUrl||"https://cdnjs.cloudflare.com/ajax/libs/rollbar.js/2.24.0/rollbar.min.js",_rollbarConfig.async=void 0===_rollbarConfig.async||_rollbarConfig.async;var a=n.setupShim(window,_rollbarConfig),l=t(_rollbarConfig);window.rollbar=n.Rollbar,a.loadFull(window,document,!_rollbarConfig.async,_rollbarConfig,l)},function(r,e,o){"use strict";function n(r){return function(){try{return r.apply(this,arguments)}catch(r){try{console.error("[Rollbar]: Internal error",r)}catch(r){}}}}function t(r,e){this.options=r,this._rollbarOldOnError=null;var o=s++;this.shimId=function(){return o},"undefined"!=typeof window&&window._rollbarShims&&(window._rollbarShims[o]={handler:e,messages:[]})}function a(r,e){if(r){var o=e.globalAlias||"Rollbar";if("object"==typeof r[o])return r[o];r._rollbarShims={},r._rollbarWrappedError=null;var t=new p(e);return n(function(){e.captureUncaught&&(t._rollbarOldOnError=r.onerror,i.captureUncaughtExceptions(r,t,!0),i.wrapGlobals(r,t,!0)),e.captureUnhandledRejections&&i.captureUnhandledRejections(r,t,!0);var n=e.autoInstrument;return e.enabled!==!1&&(void 0===n||n===!0||"object"==typeof n&&n.network)&&r.addEventListener&&(r.addEventListener("load",t.captureLoad.bind(t)),r.addEventListener("DOMContentLoaded",t.captureDomContentLoaded.bind(t))),r[o]=t,t})()}}function l(r){return n(function(){var e=this,o=Array.prototype.slice.call(arguments,0),n={shim:e,method:r,args:o,ts:new Date};window._rollbarShims[this.shimId()].messages.push(n)})}var i=o(2),s=0,d=o(3),c=function(r,e){return new t(r,e)},p=d.bind(null,c);t.prototype.loadFull=function(r,e,o,t,a){var l=function(){var e;if(void 0===r._rollbarDidLoad){e=new Error("rollbar.js did not load");for(var o,n,t,l,i=0;o=r._rollbarShims[i++];)for(o=o.messages||[];n=o.shift();)for(t=n.args||[],i=0;i<t.length;++i)if(l=t[i],"function"==typeof l){l(e);break}}"function"==typeof a&&a(e)},i=!1,s=e.createElement("script"),d=e.getElementsByTagName("script")[0],c=d.parentNode;s.crossOrigin="",s.src=t.rollbarJsUrl,o||(s.async=!0),s.onload=s.onreadystatechange=n(function(){if(!(i||this.readyState&&"loaded"!==this.readyState&&"complete"!==this.readyState)){s.onload=s.onreadystatechange=null;try{c.removeChild(s)}catch(r){}i=!0,l()}}),c.insertBefore(s,d)},t.prototype.wrap=function(r,e,o){try{var n;if(n="function"==typeof e?e:function(){return e||{}},"function"!=typeof r)return r;if(r._isWrap)return r;if(!r._rollbar_wrapped&&(r._rollbar_wrapped=function(){o&&"function"==typeof o&&o.apply(this,arguments);try{return r.apply(this,arguments)}catch(o){var e=o;throw e&&("string"==typeof e&&(e=new String(e)),e._rollbarContext=n()||{},e._rollbarContext._wrappedSource=r.toString(),window._rollbarWrappedError=e),e}},r._rollbar_wrapped._isWrap=!0,r.hasOwnProperty))for(var t in r)r.hasOwnProperty(t)&&(r._rollbar_wrapped[t]=r[t]);return r._rollbar_wrapped}catch(e){return r}};for(var u="log,debug,info,warn,warning,error,critical,global,configure,handleUncaughtException,handleUnhandledRejection,captureEvent,captureDomContentLoaded,captureLoad".split(","),f=0;f<u.length;++f)t.prototype[u[f]]=l(u[f]);r.exports={setupShim:a,Rollbar:p}},function(r,e){"use strict";function o(r,e,o){if(r){var t;"function"==typeof e._rollbarOldOnError?t=e._rollbarOldOnError:r.onerror&&!r.onerror.belongsToShim&&(t=r.onerror,e._rollbarOldOnError=t);var a=function(){var o=Array.prototype.slice.call(arguments,0);n(r,e,t,o)};a.belongsToShim=o,r.onerror=a}}function n(r,e,o,n){r._rollbarWrappedError&&(n[4]||(n[4]=r._rollbarWrappedError),n[5]||(n[5]=r._rollbarWrappedError._rollbarContext),r._rollbarWrappedError=null),e.handleUncaughtException.apply(e,n),o&&o.apply(r,n)}function t(r,e,o){if(r){"function"==typeof r._rollbarURH&&r._rollbarURH.belongsToShim&&r.removeEventListener("unhandledrejection",r._rollbarURH);var n=function(r){var o,n,t;try{o=r.reason}catch(r){o=void 0}try{n=r.promise}catch(r){n="[unhandledrejection] error getting `promise` from event"}try{t=r.detail,!o&&t&&(o=t.reason,n=t.promise)}catch(r){t="[unhandledrejection] error getting `detail` from event"}o||(o="[unhandledrejection] error getting `reason` from event"),e&&e.handleUnhandledRejection&&e.handleUnhandledRejection(o,n)};n.belongsToShim=o,r._rollbarURH=n,r.addEventListener("unhandledrejection",n)}}function a(r,e,o){if(r){var n,t,a="EventTarget,Window,Node,ApplicationCache,AudioTrackList,ChannelMergerNode,CryptoOperation,EventSource,FileReader,HTMLUnknownElement,IDBDatabase,IDBRequest,IDBTransaction,KeyOperation,MediaController,MessagePort,ModalWindow,Notification,SVGElementInstance,Screen,TextTrack,TextTrackCue,TextTrackList,WebSocket,WebSocketWorker,Worker,XMLHttpRequest,XMLHttpRequestEventTarget,XMLHttpRequestUpload".split(",");for(n=0;n<a.length;++n)t=a[n],r[t]&&r[t].prototype&&l(e,r[t].prototype,o)}}function l(r,e,o){if(e.hasOwnProperty&&e.hasOwnProperty("addEventListener")){for(var n=e.addEventListener;n._rollbarOldAdd&&n.belongsToShim;)n=n._rollbarOldAdd;var t=function(e,o,t){n.call(this,e,r.wrap(o),t)};t._rollbarOldAdd=n,t.belongsToShim=o,e.addEventListener=t;for(var a=e.removeEventListener;a._rollbarOldRemove&&a.belongsToShim;)a=a._rollbarOldRemove;var l=function(r,e,o){a.call(this,r,e&&e._rollbar_wrapped||e,o)};l._rollbarOldRemove=a,l.belongsToShim=o,e.removeEventListener=l}}r.exports={captureUncaughtExceptions:o,captureUnhandledRejections:t,wrapGlobals:a}},function(r,e){"use strict";function o(r,e){this.impl=r(e,this),this.options=e,n(o.prototype)}function n(r){for(var e=function(r){return function(){var e=Array.prototype.slice.call(arguments,0);if(this.impl[r])return this.impl[r].apply(this.impl,e)}},o="log,debug,info,warn,warning,error,critical,global,configure,handleUncaughtException,handleUnhandledRejection,_createItem,wrap,loadFull,shimId,captureEvent,captureDomContentLoaded,captureLoad".split(","),n=0;n<o.length;n++)r[o[n]]=e(o[n])}o.prototype._swapAndProcessMessages=function(r,e){this.impl=r(this.options);for(var o,n,t;o=e.shift();)n=o.method,t=o.args,this[n]&&"function"==typeof this[n]&&("captureDomContentLoaded"===n||"captureLoad"===n?this[n].apply(this,[t[0],o.ts]):this[n].apply(this,t));return this},r.exports=o},function(r,e){"use strict";r.exports=function(r){return function(e){if(!e&&!window._rollbarInitialized){r=r||{};for(var o,n,t=r.globalAlias||"Rollbar",a=window.rollbar,l=function(r){return new a(r)},i=0;o=window._rollbarShims[i++];)n||(n=o.handler),o.handler._swapAndProcessMessages(l,o.messages);window[t]=n,window._rollbarInitialized=!0}}}}]);
// End Rollbar Snippet (function(w,d,t,r,u)
{
var f,n,i;
w[u]=w[u]||[],f=function()
{
var o={ti:"343050743", enableAutoSpaTracking: true};
o.q=w[u],w[u]=new UET(o),w[u].push("pageLoad")
},
n=d.createElement(t),n.src=r,n.async=1,n.onload=n.onreadystatechange=function()
{
var s=this.readyState;
s&&s!=="loaded"&&s!=="complete"||(f(),n.onload=n.onreadystatechange=null)
},
i=d.getElementsByTagName(t)[0],i.parentNode.insertBefore(n,i)
})
(window,document,"script","//bat.bing.com/bat.js","uetq");!function(f,b,e,v,n,t,s)
{if(f.fbq)return;n=f.fbq=function(){n.callMethod?
n.callMethod.apply(n,arguments):n.queue.push(arguments)};
if(!f._fbq)f._fbq=n;n.push=n;n.loaded=!0;n.version='2.0';
n.queue=[];t=b.createElement(e);t.async=!0;
t.src=v;s=b.getElementsByTagName(e)[0];
s.parentNode.insertBefore(t,s)}(window, document,'script',
'https://connect.facebook.net/en_US/fbevents.js');
fbq('init', '927411631440706');
fbq('track', 'PageView'); <img height="1" width="1" style="display:none"
src="https://www.facebook.com/tr?id=927411631440706&ev=PageView&noscript=1"
/>!function(){
if (!window.churnkey || !window.churnkey.created) {
window.churnkey = { created: true };
const a = document.createElement('script');
a.src = 'https://assets.churnkey.co/js/app.js?appId=2l1x8e2dl';
a.async = true;
const b = document.getElementsByTagName('script')[0];
b.parentNode.insertBefore(a, b);
}
}(); <script src="https://tag.clearbitscripts.com/v1/pk_fc279c8e6fe02304f4b6e672bc239206/tags.js" referrerpolicy="strict-origin-when-cross-origin">$

PSO based LQR‐PID output feedback for load frequency control of reduced power system model using balanced truncation

Cited by 16 publications

References 31 publications

The Role of English Language and Literature in the Cultivation of Students’ Language Proficiency in the Context of Deep Learning

The Role of English Language and Literature in the Cultivation of Students’ Language Proficiency in the Context of Deep Learning

Fractional‐order PID and internal model control‐based dual‐loop load frequency control using teaching–learning optimization

Contact Info

Product

Resources

About