Intelligent Vehicle Path Tracking Control Based on Improved MPC and Hybrid PID Article Swipe
YOU?
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· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/access.2022.3203451
In this study, to improve the accuracy of path tracking in intelligent vehicles, we propose an intelligent vehicle path-tracking control method based on improved model predictive control (MPC) combined with hybrid proportional-integral-derivative (PID) control theory. In the lateral control, a constraint on the side deflection of the front wheel is added based on traditional MPC and a relaxation factor is introduced to improve the stability of vehicle control for the driving stability. In longitudinal control, a hybrid PID controller is designed for different road conditions to improve the accuracy of control of vehicle speed. We present the results of a co-simulation using Carim and MATLAB/Simulink and a test with a sample vehicle, which show that the proposed path tracking controller can greatly improve the path tracking accuracy and stability of an intelligent vehicle. The model-based prediction, rolling optimization solution, feedback control, and the addition of a constraint on the side deflection of the front wheel as well as a relaxation factor can ensure the lateral driving stability of an intelligent vehicle. The proposed approach achieved a lateral error of less than 1%, and the yaw angle was controlled within 4°. The longitudinal speed control based on hybrid PID controller can improve the response speed of the system and meet the real-time requirements of vehicle driving.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2022.3203451
- https://ieeexplore.ieee.org/ielx7/6287639/6514899/09874852.pdf
- OA Status
- gold
- Cited By
- 51
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4294167390
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4294167390Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/access.2022.3203451Digital Object Identifier
- Title
-
Intelligent Vehicle Path Tracking Control Based on Improved MPC and Hybrid PIDWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-01-01Full publication date if available
- Authors
-
Peicheng Shi, Long Li, Xuan Ni, Aixi YangList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2022.3203451Publisher landing page
- PDF URL
-
https://ieeexplore.ieee.org/ielx7/6287639/6514899/09874852.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://ieeexplore.ieee.org/ielx7/6287639/6514899/09874852.pdfDirect OA link when available
- Concepts
-
Control theory (sociology), PID controller, CarSim, Model predictive control, Computer science, MATLAB, Vehicle dynamics, Controller (irrigation), Deflection (physics), Electronic stability control, Control system, Control engineering, Engineering, Automotive engineering, Control (management), Temperature control, Artificial intelligence, Optics, Physics, Agronomy, Operating system, Biology, Electrical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
51Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 21, 2024: 18, 2023: 11, 2022: 1Per-year citation counts (last 5 years)
- References (count)
-
24Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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