Design and Implementation of Parallel Fuzzy PID Controller for High-Performance Brushless Motor Drives: An Integrated Environment for Rapid Control Prototyping

• Published in: IEEE transactions on industry applications Vol. 44; no. 4; pp. 1090 - 1098
• Main Authors: Rubaai, A., Castro-Sitiriche, M.J., Ofoli, A.R.
• Format: Journal Article
• Language: English
• Published: New York IEEE 2008; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Architecture; Brushless motors; Classical proportional-integral-derivative (PID) control; Control nonlinearities; Control systems; Controllers; Design engineering; dSPACE digital signal processor (DSP); Fuzzy; Fuzzy control; Fuzzy logic; Fuzzy set theory; hybrid fuzzy PID controller; Matlab; MATLAB/Simulink; Pi control; Proportional control; Proportional integral derivative; Prototypes; Real time systems; Robust control; robustness; Studies; Three-term control
• ISSN: 0093-9994; 1939-9367
• DOI: 10.1109/TIA.2008.926059

This paper presents an integrated environment for the rapid prototyping of a robust fuzzy proportional-integral-derivative (PID) controller that allows rapid realization of novel designs. Both the design of the fuzzy PID controller and its integration with the classical PID in a global control system are developed. The architecture of the fuzzy PID controller is basically composed of three parallel fuzzy subcontrollers. Then, the parallel subcontrollers are grouped together to form the overall fuzzy PID controller. The fuzzy proportional, integral, and derivative gains are direct output from the parallel fuzzy subcontrollers and are derived in the error domain. Thus, the proposed architecture presents an alternative to control schemes employed so far. The integrated controller is formulated and implemented in real time, using the speed control of a brushless drive system as a test bed. The design, analysis, and implementation stages are carried out entirely using a dSPACE DS1104 digital-signal-processor-based real-time data acquisition control system and MATLAB/Simulink environment. Experimental results show that the proposed hybrid fuzzy PID controller produces superior control performance than the conventional PID controllers, particularly in handling nonlinearities and external disturbances.