Compound control for electromagnetic linear load simulator

Abstract

Electromagnetic linear load simulator (ELLS) is a device that simulates the load force on the load bearing object. This paper proposes a new compound control method based on the combination of neural network algorithm and feedforward compensation principle to improve force loading performance of ELLS. First, the mathematical model of the force loading system and the problem formulation is introduced. Then, radial basis function (RBF) neural network algorithm, single neuron proportional–integral–derivative (PID) control algorithm, and feedforward compensation principle are presented. Based on these control theories, a compound controller is designed and the block diagram of the proposed method for force loading system is presented. In order to verify the superiority of compound control, different control methods are compared in simulation and experiment under different operating conditions. It is clearly demonstrated that the proposed compound control method has better dynamic and static characteristics, and meet the established control requirements.