By Topic

DSP-Based Implementation of Fuzzy-PID Controller Using Genetic Optimization for High Performance Motor Drives

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
$31 $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

3 Author(s)
Rubaai, A. ; Howard Univ., Washington ; Castro-Sitiriche, M.J. ; Ofoli, A.

This paper presents a real-time implementation of a genetic-based hybrid fuzzy-PID controller for industrial motor drives. Both the design of fuzzy-PID controller and its integration with the conventional PID in global control system to produce a hybrid design is demonstrated. A genetic optimization technique is used to determine the optimal values of the scaling factors of the output variables of the fuzzy-PID controller. The objective is to utilize the best attributes of the PID and fuzzy-PID controllers to provide a controller, which will produce better response than either the PID or the fuzzy-PID controller. The principle of the hybrid controller is to use a PID controller, which performs satisfactorily in most cases, while keeping in the background, a fuzzy-PID controller, which, is ready to take over the PID controller when severe disturbs occur. The hybrid controller is formulated and implemented in real-time, using the speed control of a brushless drive system as a testbed. The design, analysis, and implementation stages are carried out entirely using a dSPACE DS1104 digital signal processor (DSP)-based real-time data acquisition control (DAC) system, and MATLAB/Simulink environment. Experimental results show that the proposed fuzzy- PID controller-based genetic optimization produces better control performance than the conventional PID controllers, particularly in handling nonlinearities and external disturbances.

Published in:

Industry Applications Conference, 2007. 42nd IAS Annual Meeting. Conference Record of the 2007 IEEE

Date of Conference:

23-27 Sept. 2007