Title :
Direct adaptive regulation using dynamic neural networks: application to DC motors
Author :
Rovithakis, George A. ; Christodoulou, Manolis A.
Author_Institution :
Dept. of Electron. & Comput. Eng., Tech. Univ. of Crete, Chania, Greece
Abstract :
A direct nonlinear adaptive state regulator is derived, based on dynamic neural networks and it is successfully applied to control the speed of a nonlinearized DC motor. One interesting feature of the proposed control algorithm is that it covers the situation where the magnetic flux continuously varies, as it is the case in the loss minimization problem
Keywords :
DC motors; adaptive control; digital control; losses; machine control; magnetic flux; neural nets; power engineering computing; velocity control; DC motors; continuously varying magnetic flux; direct adaptive regulation; dynamic neural networks; loss minimization; nonlinear adaptive state regulator; nonlinearized DC motor; speed control; Adaptive control; Application software; Backpropagation; Control systems; DC motors; Linear feedback control systems; Neural networks; Programmable control; Regulators; Sliding mode control;
Conference_Titel :
Industrial Electronics, 1995. ISIE '95., Proceedings of the IEEE International Symposium on
Conference_Location :
Athens
Print_ISBN :
0-7803-7369-3
DOI :
10.1109/ISIE.1995.497024
