Title :
Intelligent coordination steering control of automated guided vehicle
Author :
Zhan, Yue Dong ; Guo, You Guang ; Zhu, Jian Guo
Author_Institution :
Dept. of Autom., Kunming Univ. of Sci. & Technol., Kunming, China
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.
Keywords :
automatic guided vehicles; bang-bang control; control system synthesis; fuzzy control; identification; least squares approximations; neurocontrollers; AGV controller design; AGV model parameters; AGV steering system; automated guided vehicle; bang-bang control; distance error; dynamic performance improvement; dynamic steering model; fuzzy control; intelligent coordination steering control; least squares method; neural network; orientation angle error; system identification; Artificial intelligence; Artificial neural networks; Autoregressive processes; Control systems; Fuzzy control; Mathematical model; Wheels; automated guided vehicle (AGV); fuzzy control; intelligent coordination control; neural network control;
Conference_Titel :
Applied Superconductivity and Electromagnetic Devices (ASEMD), 2011 International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4244-7852-1
DOI :
10.1109/ASEMD.2011.6145101
