Front wheel angle tracking control research of intelligent heavy vehicle steering system

This paper conducts the front wheel angle tracking compensation control of the electro-hydraulic coupling power steering system (EHCPS) of the intelligent heavy vehicle (IHV). It has been found from the results of mathematic analysis, simulation and open-loop frequency test of the EHCPS that front wheel angle slightly lags behind handwheel angle at low frequencies. In this paper, a kind of fuzzy neural network controller (FNNC) based on model reference adaptive control (MRAC) is designed. Fuzzy neural network is also used to identify the EHCPS on-line. Membership function and inference rules of the FNNC and fuzzy neural network identification (FNNI) are renewed by the self-learning function of neural network to achieve on-line regulation of controller's parameters. Reference model with certain bandwidth and control algorithm are designed to ensure that actual front wheel angle follows desired front wheel angle. Finally, the hardware-in-the-loop experiment and simulation results indicate that the control strategy presented in this paper is effective in compensating front wheel angle tracking within certain bandwidth of EHCPS.