Intelligent coordination steering control of automated guided vehicle

Abstract

In this paper, based on the neural network, fuzzy control and bang-bang control, an intelligent coordination control strategy for automated guided vehicle (AGV) steering system is presented. The dynamic steering model of distance error and orientation angle error for AGV is expressed. With least square method of system identification, the model of AGV is identified. Because a toy type of AGV is employed, its structure is simple, but AGV model parameters are variable according to the operating conditions and environment. In order to improve the dynamic performances of AGV, the intelligent coordinated control strategy is used to design the AGV controller in the AGV steering control system. Simulation and experimental results show the effectiveness of the proposed control strategy. © 2011 IEEE