Motor-driven load system based on neural networks

Aiming at the disturbance of extraneous force in the motor-driven load system, a new composite control strategy based on Radial Basis Function (RBF) networks is proposed. Compared with the controllers based on conventional BP networks, the presented algorithm is much more efficient for not having the problem of local minima. The motor-driven load system is highly nonlinear and includes delays in the control loop. It is difficult for the traditional control method such as PID to improve the performance, especially under the disturbance of movement, i.e., the so-called extraneous force problem. The proposed composite control scheme consists of NN PID and feedforward compensator. The experimental result shows that the scheme compensates the extraneous force effectively and improves the dynamic performance of the load system.