Title :
Robust control for nonlinear motor-mechanism coupling system using wavelet neural network
Author_Institution :
Dept. of Electr. Eng., Yuan Ze Univ., Chung-li, Taiwan
fDate :
6/1/2003 12:00:00 AM
Abstract :
A robust controlled toggle mechanism, which is driven by a permanent magnet (PM) synchronous servo motor is studied in this paper. First, based on the principle of computed torque control, a position controller is developed for the motor-mechanism coupling system. Moreover, to relax the requirement of the lumped uncertainty in the design of a computed torque controller, a wavelet neural network (WNN) uncertainty observer is utilized to adapt the lumped uncertainty online. Furthermore, based on the Lyapunov stability a robust control system, which combines the computed torque controller, the WNN uncertainty observer and a compensated controller is proposed to control the position of the motor-mechanism coupling system. The computed torque controller with WNN uncertainty observer is the main tracking controller, and the compensated controller is designed to compensate the minimum approximation error of the uncertainty observer. Finally, simulated and experimental results due to a periodic sinusoidal command show that the dynamic behaviors of the proposed robust control system are robust with regard to parametric variations and external disturbances.
Keywords :
adaptive control; neural nets; observers; position control; robust control; servomotors; torque control; wavelet transforms; Lyapunov stability; computed torque controller; lumped uncertainty; permanent magnet; position controller; robust control; synchronous servo motor; toggle mechanism; torque control; uncertainty observer; wavelet neural network; Control systems; Couplings; Neural networks; Permanent magnet motors; Robust control; Servomechanisms; Servomotors; Synchronous motors; Torque control; Uncertainty;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2003.811125