@inproceedings{73608cf2fda3492f9bd0d1849414a182,
title = "Research on Unmanned Vehicle Stability Control with Model Prediction Control",
abstract = "The use of ESC(Electronic Stability Control) significantly improves vehicle stability. Most ESC systems keep the vehicle stable by limiting raw rate and lateral velocity of the vehicle in a particular range. However, this method does not suitable for the unmanned vehicle. If the environment is very complicated, the ESC may misjudge. It is necessary to consider the unmanned vehicle condition over a short period of time to determine the true state of the unmanned vehicle. Different models should be established according to all states of the unmanned vehicle, and then the predicted results of these models can be compared to choose the result closest to the data measured by the sensor. Based on the selected model, the current best control strategy can be obtained. Experiments have been conducted under a variety of conditions. The results show that the stability control system using model prediction control(MPC) can effectively improve the stability of the vehicle.",
keywords = "model prediction, stability, unmanned vehicle",
author = "Ji Zhang and Hui Jin",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 4th International Conference on Control and Robotics Engineering, ICCRE 2019 ; Conference date: 20-04-2019 Through 23-04-2019",
year = "2019",
month = apr,
doi = "10.1109/ICCRE.2019.8724349",
language = "English",
series = "4th International Conference on Control and Robotics Engineering, ICCRE 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "12--15",
booktitle = "4th International Conference on Control and Robotics Engineering, ICCRE 2019",
address = "United States",
}