By Topic

Adaptive sliding mode speed control of surface permanent magnet synchronous motor using input-output feedback linearization

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Sayed Mahdi Fazeli ; Faculty of Engineering, University of Malaya, Kuala-Lumpur, Malaysia ; Hossein Abootorabi Zarchi ; Jafar Soltani ; Hew Wooi Ping

A nonlinear adaptive robust speed tracking controller is presented for a three-phase surface permanent magnet synchronous motor (SPSMS) considering the control strategy of maximum torque control (MTC) related to this motor. Ignoring the motor iron losses, the proposed controller is designed based on combination of input-output feedback linearization (IOFL) control and adaptive sliding mode technique. The proposed adaptive sliding mode controller estimates the unknown uncertainties without using sign(.) or sat(.) function. Hence, it reduces chattering or steady state error phenomenon. In addition, in order to make the drive system control robust to load torque disturbance, the stator current reference signal is predicted by another adaptive sliding mode controller that has a low sliding mode chattering. Finally, the effectiveness and feasibility of the proposed control approach is demonstrated by computer simulation. The results obtained confirm that the desired speed reference command is perfectly tracked in spite of motor parameter uncertainties and load torque disturbance.

Published in:

Electrical Machines and Systems, 2008. ICEMS 2008. International Conference on

Date of Conference:

17-20 Oct. 2008