Title :
Discrete-Time Neural Sliding-Mode Block Control for a DC Motor With Controlled Flux
Author :
Castaneda, Carlos E. ; Loukianov, Alexander G. ; Sanchez, Edgar N. ; Castillo-Toledo, Bernardino
Author_Institution :
Centro Univ. de los Lagos, Univ. de Guadalajara, Lagos de Moreno, Mexico
Abstract :
An adaptive discrete-time tracking controller for a direct current motor with controlled excitation flux is presented. A recurrent neural network is used to identify the plant model; this neural identifier is trained with an extended Kalman filter algorithm. Then, the discrete-time block-control and sliding-mode techniques are used to develop the trajectory tracking. This paper also includes the respective stability analysis for the whole closed-loop system. The effectiveness of the proposed control scheme is verified via real-time implementation.
Keywords :
DC motors; Kalman filters; adaptive control; closed loop systems; discrete time systems; machine control; neurocontrollers; nonlinear filters; position control; recurrent neural nets; stability; variable structure systems; adaptive controller; closed-loop system; controlled excitation flux; dc motor; direct current motor; discrete-time neural control; extended Kalman filter algorithm; neural identifier; plant model; recurrent neural network; sliding-mode block control; stability analysis; tracking controller; trajectory tracking; Adaptation models; Artificial neural networks; Covariance matrix; DC motors; Kalman filters; Load modeling; Torque; Direct current (dc) motor; neural networks (NNs); sliding-mode (SM) control;
Journal_Title :
Industrial Electronics, IEEE Transactions on
DOI :
10.1109/TIE.2011.2161246
