Title :
Artificial neural network as a gain scheduler for PI speed controller in DC motor drives
Author :
Kulic, Filip ; Kukolj, Dragan ; Levi, Emil
Author_Institution :
Dept. of Electr. Eng., Novi Sad Univ., Serbia
Abstract :
The paper proposes an application of artificial neural network (ANN) as a gain scheduler for a conventional PI speed controller. A comparative analysis of the DC motor drive behaviour, controlled by a conventional PI speed controller with and without ANN based gain scheduling, is performed. It is shown that the gain scheduling by a suitably trained ANN enables very good quality of the drive performance over a wide range of operating conditions. The achievable quality of performance is superior to the one obtainable without gain scheduling. Verification of the proposed DC motor speed control system is provided by extensive simulation
Keywords :
DC motor drives; learning (artificial intelligence); neurocontrollers; two-term control; velocity control; DC motor drives; PI controller; gain scheduling; learning; neural network; neurocontrol; speed control; Artificial neural networks; Control systems; DC motors; Drives; Electric variables control; Intelligent networks; Multilayer perceptrons; Performance gain; Processor scheduling; Velocity control;
Conference_Titel :
Neural Network Applications in Electrical Engineering, 2000. NEUREL 2000. Proceedings of the 5th Seminar on
Conference_Location :
Belgrade
Print_ISBN :
0-7803-5512-1
DOI :
10.1109/NEUREL.2000.902412