Study Of Multi-motor Synchronization System With Neural Network Control Based On S7-300

The paper focuses on the multi-variable decoupling control of synchronization system of the AC induction motors. With the application of neural network control method, we make researches on the decoupling control between the velocity and tension of the two-motor synchronization system composed of two AC induction motors and transducers.On the basis of model analysis of the two-motor synchronization system, according to the structural character and controlling requests of the synchronization system, we put forward a new control strategy of the two-motor synchronization system based on artificial neural networks combined with its nonlinear mapping capability, adaptive and learning capability. The neural network controller is composed of adaptive PID controller using the RBF networks to modulate and neuron decoupling compensator. The two adaptive PID controllers are used in the velocity control loop and tension control loop respectively, that make the system possessing stronger adaptive capability and other better performances. The neuron decoupling compensator integrates the effects of the two loops each other and realizes the decoupling control between velocity and tension by training the weights of networks to compensate the coupling relation.The whole arithmetic of neural network control is carried out by the S7-300 PLC of Siemens.The software of STEP7 may compile neural network control program high effectively with its structural compiling method. In addition, we still set up the PROFIBUS-DP communication between PLC and transducers, MPI communication between WINCC and PLC. So we realize the long-distance intellectualized control of the whole two-motor synchronization system.Finally, we perform experiments on the platform of multi-motor synchronization system. Lots of experimental results indicate that the neural network control scheme has realized the decoupling control between the velocity and tension of the two-motor synchronization system with better dynamic and static characteristics. The control method proposed in the paper is promising and can be applied in many industrial control environments.