The control system of electric load simulator based on neural network

Abstract

The superfluous torque is a key issue on electric load simulator. How to overcome the superfluous force is the critical issue for designing load simulator and improving control system performance. In this paper, the electric load modeling on the basis of the RBF neural network algorithm for system identification of the system model and the PID parameters, real-time updates PID control parameters to ensure that the system dynamic and static characteristics. And through simulation, the controller reduces the excess torque on the system. © 2012 Springer-Verlag GmbH.