Title :
Observer-based differential algebraic neural network nonlinear control of PM synchronous motor
Author :
Huiyan, Li ; Jiang, Wang ; Zheng Pie
Author_Institution :
Sch. of Manage., Tianjin Univ., China
Abstract :
The mathematical model of the PMSM with nonlinear field and friction is presented, the model of the PMSM is linearized by the differential algebraic strategy, neural network is approximated nonlinear function and external disturbance, then forward and feedback control is made position close loop. The current and velocity are observed using the nonlinear high-gain observers. The stability of the controller-observer system, which is composed of controllers and observers, is verified by the Lyapunov theory. Simulation studies are done to demonstrate the effectiveness of the proposed control strategy.
Keywords :
Lyapunov methods; closed loop systems; feedback; linearisation techniques; machine control; neurocontrollers; nonlinear control systems; nonlinear functions; observers; permanent magnet motors; position control; stability; synchronous motors; Lyapunov theory; differential algebraic neural network; feedback control; forward control; nonlinear control; nonlinear function; nonlinear high gain observers; permanent magnet synchronous motor; position close loop; stability; Automatic control; Automation; Control systems; Electronic mail; Feedforward neural networks; Friction; Linear feedback control systems; Mathematical model; Neural networks; Synchronous motors;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1342352
