Abstract：On the basis of model analysis of the two-motor synchronous system, according to the structural characteristic and control request of the system, a new control strategy based on neural networks is presented combined with its nonlinear mapping and adaptive and self-learning capabilities. The neural network controller is composed of adaptive PID controller, which uses the RBF network to modulate and the neuron decoupling compensator. The two adaptive PID controllers are used in the velocity loop and tension loop respectively, which make the system possess stronger adaptive capability and other better performances. The neuron decoupling compensator integrates the coupling effects of the two loops and realizes the decoupling control between velocity and tension by training the weights of networks to compensate the coupling effects. The experimental results show that the two-motor synchronous system is decoupled based on neural network control with better dynamic and static characteristics.
2008, Vol. 29 
