@article{ART003139160},
author={Kap Rai Lee},
title={Deep Learning-based PID Control for ETB with Parameter Variation and Nonlinear Torque},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={11},
pages={57-66},
doi={10.9708/jksci.2024.29.11.057}
TY - JOUR
AU - Kap Rai Lee
TI - Deep Learning-based PID Control for ETB with Parameter Variation and Nonlinear Torque
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 11
PB - The Korean Society Of Computer And Information
SP - 57
EP - 66
SN - 1598-849X
AB - In this paper, an approach based on deep learning and parameter dependent control is proposed for electronic throttle body(ETB) control which has variable parameters and nonlinear torques. Firstly we present parameter estimation method for ETB system using deep neural network. To estimate parameters of ETB, we design deep neural networks and train by use time response characteristic such as rise time, overshoot and settling time. Parameters of ETB are estimated through trained neural networks by using time response data. Secondly we design parameter dependent PID controller which is adjusted automatically with the estimated system parameter of ETB. To design optimal parameter dependent gain of PID controller, we use ITAE(Integral of time multiplied by absolute error) criteria. In addition, we design feed-forward controller to reject nonlinear torque. Finally we present simulation results of ETB syatem with parameter variation and nonlinear torque to verify controller design method.
KW - Electronic throttle body;Time invariant parameter variation;Nonlinear torque;Deep learning based control;Parameter dependent PID Controller
DO - 10.9708/jksci.2024.29.11.057
ER -
Kap Rai Lee. (2024). Deep Learning-based PID Control for ETB with Parameter Variation and Nonlinear Torque. Journal of The Korea Society of Computer and Information, 29(11), 57-66.
Kap Rai Lee. 2024, "Deep Learning-based PID Control for ETB with Parameter Variation and Nonlinear Torque", Journal of The Korea Society of Computer and Information, vol.29, no.11 pp.57-66. Available from: doi:10.9708/jksci.2024.29.11.057
Kap Rai Lee "Deep Learning-based PID Control for ETB with Parameter Variation and Nonlinear Torque" Journal of The Korea Society of Computer and Information 29.11 pp.57-66 (2024) : 57.
Kap Rai Lee. Deep Learning-based PID Control for ETB with Parameter Variation and Nonlinear Torque. 2024; 29(11), 57-66. Available from: doi:10.9708/jksci.2024.29.11.057
Kap Rai Lee. "Deep Learning-based PID Control for ETB with Parameter Variation and Nonlinear Torque" Journal of The Korea Society of Computer and Information 29, no.11 (2024) : 57-66.doi: 10.9708/jksci.2024.29.11.057
Kap Rai Lee. Deep Learning-based PID Control for ETB with Parameter Variation and Nonlinear Torque. Journal of The Korea Society of Computer and Information, 29(11), 57-66. doi: 10.9708/jksci.2024.29.11.057
Kap Rai Lee. Deep Learning-based PID Control for ETB with Parameter Variation and Nonlinear Torque. Journal of The Korea Society of Computer and Information. 2024; 29(11) 57-66. doi: 10.9708/jksci.2024.29.11.057
Kap Rai Lee. Deep Learning-based PID Control for ETB with Parameter Variation and Nonlinear Torque. 2024; 29(11), 57-66. Available from: doi:10.9708/jksci.2024.29.11.057
Kap Rai Lee. "Deep Learning-based PID Control for ETB with Parameter Variation and Nonlinear Torque" Journal of The Korea Society of Computer and Information 29, no.11 (2024) : 57-66.doi: 10.9708/jksci.2024.29.11.057
