Research on Dynamic Variable Transmission Ratio and Handling Stability for Steer by Wire Vehicle Based on Neural Network

The handling stability and control requirements of electric forklift are analyzed. Forklift model with linear two degree of freedom (2DOF) is presented, which provides a verification model for variable transmission ratio (VTR) design. The concept of the ideal transmission ratio is described, the VTR control method based on yaw rate gain constant and lateral acceleration gain constant is studied, a new VTR control method based on two kinds of gain constant combination is put forward, and the simulation comparison is made for three kinds of static VTR control methods. A dynamic VTR control method based on fuzzy neural network (FNN) is designed for complex working conditions, simulation results show that the VTR based on FNN has strong resistance to the disturbance of its own parameters. It is only related to the velocity and the hand-wheel angle, and adapts to the complex dynamic conditions, helps to improve the handling stability of forklift. The research shows that the three VTR control methods with fixed gain are derived through mathematical model, which belongs to static control, and the dynamic VTR control method based on FNN has better dynamic adaptability.