{"title":"An Adaptive Variable Structure Control Law for Sensorless Induction Motors","authors":"Oscar Barambones, Aitor J. Garrido","doi":"10.3166/ejc.13.382-392","DOIUrl":null,"url":null,"abstract":"<div><p>This paper presents a new sensorless adaptive robust control for induction motor drives. The proposed design employs the so called vector (or field oriented) control theory for the induction motor drives and the designed control law is based on an integral sliding-mode algorithm that overcomes the system uncertainties. The proposed sliding-mode control law incorporates an adaptive switching gain that avoid calculating an upper limit of the system uncertainties. The design includes rotor speed estimation from measured stator terminal voltages and currents. The estimated speed is used as feedback in an indirect vector control system in order to achieve the speed control without the use of shaft mounted transducers. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally simulated results show on the one hand that the proposed controller with the proposed observer provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external load disturbances.</p></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"13 4","pages":"Pages 382-392"},"PeriodicalIF":2.6000,"publicationDate":"2007-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3166/ejc.13.382-392","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Control","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0947358007708324","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 20
Abstract
This paper presents a new sensorless adaptive robust control for induction motor drives. The proposed design employs the so called vector (or field oriented) control theory for the induction motor drives and the designed control law is based on an integral sliding-mode algorithm that overcomes the system uncertainties. The proposed sliding-mode control law incorporates an adaptive switching gain that avoid calculating an upper limit of the system uncertainties. The design includes rotor speed estimation from measured stator terminal voltages and currents. The estimated speed is used as feedback in an indirect vector control system in order to achieve the speed control without the use of shaft mounted transducers. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally simulated results show on the one hand that the proposed controller with the proposed observer provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external load disturbances.
期刊介绍:
The European Control Association (EUCA) has among its objectives to promote the development of the discipline. Apart from the European Control Conferences, the European Journal of Control is the Association''s main channel for the dissemination of important contributions in the field.
The aim of the Journal is to publish high quality papers on the theory and practice of control and systems engineering.
The scope of the Journal will be wide and cover all aspects of the discipline including methodologies, techniques and applications.
Research in control and systems engineering is necessary to develop new concepts and tools which enhance our understanding and improve our ability to design and implement high performance control systems. Submitted papers should stress the practical motivations and relevance of their results.
The design and implementation of a successful control system requires the use of a range of techniques:
Modelling
Robustness Analysis
Identification
Optimization
Control Law Design
Numerical analysis
Fault Detection, and so on.