@inproceedings{5e639b3093134e1aa684dd4101dded13,
title = "Trajectory tracking automated guided vehicle using fuzzy controller",
abstract = "This paper proposes the development of a fuzzy controller and a nonlinear dynamics feedback to minimize error in tracking nonsmooth trajectory for an Automated Guided Vehicle with nonholonomic constraints. The AGV is designed using differential drive for small material transportation handling in manufacture area productions. In order to minimize the tracking error from the reference trajectory with quick turn points and initial position error, the fuzzy controller is used to determine input auxiliary velocity for dynamics controller. The fuzzy controller is designed using parallel distributed compensation with 3 state kinematic error model. The stability of the controller is guaranteed by Lyapunov theory using LMI (Linear Matrix Inequality) solver. The dynamics controller is designed with a nonlinear dynamics feedback using forward gain and proportional-derivative control that used to obtain the input torque for AGV. Simulation results show that the AGV can track sudden big orientation change from the nonsmooth reference trajectory and initial position error.",
keywords = "AGV, LMI, auxiliary velocity, control, fuzzy",
author = "Mamat Septyan and Trihastuti Agustinah",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 1st International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019 ; Conference date: 13-03-2019 Through 15-03-2019",
year = "2019",
month = mar,
doi = "10.1109/ICAIIT.2019.8834575",
language = "English",
series = "Proceeding - 2019 International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "169--174",
booktitle = "Proceeding - 2019 International Conference of Artificial Intelligence and Information Technology, ICAIIT 2019",
address = "United States",
}