Title :
Application of Artificial Neural Network to Robust Speed Control of Servodrive
Author :
Pajchrowski, Tomasz ; Zawirski, Krzysztof
Author_Institution :
Inst. of Control & Inf. Eng., Tech. Univ. Poznan
Abstract :
This paper deals with the problem of robust speed control of electrical servodrives. A robust speed controller is developed using an artificial neural network (ANN), which creates a nonlinear characteristic of controller. An original method of neural controller synthesis is presented. The synthesis procedure is performed in two stages. The first stage consists in training the ANN and at the second stage controller settings are adjusted. The use of the proposed controller synthesis procedure ensures robust speed control against the variations of moment of inertia and stator magnetic flux. Simulations and laboratory results validate the robustness of the servodrive with permanent magnet synchronous motor
Keywords :
angular velocity control; control system synthesis; learning (artificial intelligence); machine control; magnetic flux; neurocontrollers; nonlinear control systems; permanent magnet motors; robust control; servomotors; stators; synchronous motor drives; artificial neural network; electrical servodrives; moment of inertia; neural controller synthesis; neural net training; nonlinear characteristics; permanent magnet synchronous motor; robust speed controller; stator magnetic flux; Artificial neural networks; Control systems; Magnetic flux; Network synthesis; Permanent magnet motors; Robust control; Robustness; Sliding mode control; Stators; Velocity control; Neural network applications; permanent magnet motors; robustness;
Journal_Title :
Industrial Electronics, IEEE Transactions on
DOI :
10.1109/TIE.2006.888782