TitleHigh performance backstepping control of induction motor with adaptive sliding mode observer
Journal titleArchives of Control Sciences
Divisions of PASNauki Techniczne
Archives of Control Sciences welcomes for consideration papers on topics of significance in broadly understood control science and related areas, including: basic control theory, optimal control, optimization methods, control of complex systems, mathematical modeling of dynamic and control systems, expert and decision support systems and diverse methods of knowledge modelling and representing uncertainty (by stochastic, set-valued, fuzzy or rough set methods, etc.), robotics and flexible manufacturing systems. Related areas that are covered include information technology, parallel and distributed computations, neural networks and mathematical biomedicine, mathematical economics, applied game theory, financial engineering, business informatics and other similar fields.
Aims and Scope: Archives of Control Sciences publishes papers in the broadly understood field of control science and related areas while promoting the closer integration of the Polish, as well as other Central and East European scientific communities with the international world of science.
AbstractHigh performance backstepping control of induction motor with adaptive sliding mode observer It is well known that modern control of induction motor relies on a good dynamic model of the motor. Extensive research and activity have been devoted to the problem of induction motor control over the last decade. In this paper we introduce backstepping control with amelioration of performance to guarantee stability of the system. Accurate knowledge of the rotor speed and flux position is the key factor in obtaining a high-performance and high-efficiency induction-motor drive. Thus a sliding mode observer design is presented. Simulation results are included to illustrate good performance of backstepping control of sensorless induction motors with flux observer.
PublisherCommittee of Automatic Control and Robotics PAS
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