Modeling And Control Of Ac Machine Using Matlab?/Simulink, 1St Edition

This book introduces electrical machine modeling and control for electrical engineering and science to graduate, undergraduate students as well as researchers, who are working on modeling and control of electrical machines. It targets electrical engineering students who have no time to derive mathematical equations for electrical machines in particular induction machine (IM) and doubly fed induction machines (DFIM).

The main focus is on the application of field oriented control technique to induction motor (IM) and doubly fed induction motor (DFIM) in details, and since the induction motors have many drawback using this technique, therefore the application of a nonlinear control technique (feedback linearization) is applied to a reduced order model of DFIM to enhance the performance of doubly fed induction motor.

Features

• Serves as text book for electrical motor modeling, simulation and control; especially modeling of induction motor and doubly fed induction motor using different frame of references.
• Vector control (field oriented control) is given in more detailed, and is applied to induction motor.
• A nonlinear controller is applied to a reduced model of an doubly induction motor associated with a linear observer to estimate the unmeasured load torque, which is used to enhance the performance of the vector control to doubly fed induction motor.
• Access to the full MATLAB/SIMULINK blocks for simulation and control.

Mourad Boufadene received his Electrical Engineering degree major in computer science from the University of Boumerdes (formely INELEC) in June 2009. In 2012, he received his Magister degree in Electrical Engineering major in automatic option advance control for complex systems, from Ecole National Polytechnique Oran, Algeria (formerly ENSET). In 2018, he received his doctoral degree from the University of Amar Teldji Laghouat, Algeria. His research interests include adaptive nonlinear observers, nonlinear control of complex systems such as feedback linearization and sliding mode control, artificial intelligence and electrical machine control, diagnosis and observation of complex systems such as vehicles.