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Yaw Feedback Control of Active Steering Vehicle Based on Differential Flatness Theory
1
The 4th International Conference on Material Strength and Applied Mechanics (MSAM 2021) Conference Secretary, China
2
Logistics Engineering College, Shanghai Maritime University, Shanghai, China
3
Key Laboratory of Railway Industry of Maglev Technology, Tongji University, Shanghai, China
4
National Maglev Transportation Engineering R&D Center, Tongji University, Shanghai, China
Submission date: 2024-07-14
Final revision date: 2024-10-09
Acceptance date: 2024-11-08
Online publication date: 2025-01-27
Corresponding author
Yougang Sun
National Maglev Transportation Engineering R&D Center, Tongji University, Shanghai, China
National Maglev Transportation Engineering R&D Center, Tongji University, Shanghai, China
KEYWORDS
TOPICS
robotic and control systemsstability and vibrations systemsdynamics of machines, vehicles and flying structuresinteligent systems
ABSTRACT
In order to solve the problems of nonlinearity, underactuation and insufficient lateral stability of an active steering vehicle (ASV) in trajectory tracking tasks, a yaw feedback control strategy based on differential flatness theory is proposed in this paper. Firstly, the vehicle integrated monorail model is established, and the vehicle model is linearized by small angle approximation. Secondly, a suitable flat output is found to convert a complex vehicle model into a full drive system, and the flatness of the linear model is proved. Then, an equivalent form of the vehicle model is constructed based on the flat output and its derivatives, and a feedback controller based on the differential flat theory is designed to complete the trajectory tracking control through active steering and longitudinal motion. Finally, an ASV control simulation model is built in MATLAB/Simulink, and the simulation results show the effectiveness of the proposed control strategy under different maneuvering conditions.
REFERENCES (25)
1.
Aschemann H., Schindele D., 2008, Sliding-mode control of a high-speed linear axis driven by pneumatic muscle actuators, IEEE Transactions on Industrial Electronics, 55, 11, 3855-3864.
2.
Bai G.X., Liu L., Meng Y., Luo W.D., Gu Q., Ma B.Q., 2019, Path tracking of mining vehicles based on nonlinear model predictive control, Applied Sciences, 9, 7, 1372.
3.
Elmi N., Ohadi A., Samadi B., 2013, Active front-steering control of a sport utility vehicle using a robust linear quadratic regulator method, with emphasis on the roll dynamics, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 227, 12, 1636-1649.
4.
Fliess M., Lévine J., Martin P., Rouchon P., 1995, Flatness and defect of nonlinear systems: Introductory theory and examples, International Journal of Control, 61, 6, 1327-1361.
5.
Guerrero J., Chemori A., Torres J., Creuze V., 2023, Time-delay high-order sliding mode control for trajectory tracking of autonomous underwater vehicles under disturbances, Ocean Engineering, 268, 113375.
6.
Huang C.Z., Luo C.M., Li Y., Zhang T.Y., 2019, Differential flatness active disturbance rejection control approach for a class of nonlinear uncertain systems, International Journal of Robotics and Automation, 34, 2, 146-155.
7.
Kang N., Han Y., Guan T., Wang S., 2022, Improved ADRC-based autonomous vehicle path-tracking control study considering lateral stability, Applied Sciences, 12, 9, 4660.
8.
Li Z., Li J., Wang W., 2023, Path planning and obstacle avoidance control for autonomous multi-axis distributed vehicle based on dynamic constraints, IEEE Transactions on Vehicular Technology, 72, 4, 4342-4356.
9.
Luo L., Cao S.Y., Sheng Z., Shen H.L., 2022, LiDAR-based global localization using histogram of orientations of principal normals, IEEE Transactions on Intelligent Vehicles, 7, 3, 771-782.
10.
Mata S., Zubizarreta A., Pinto C., 2019, Robust tube-based model predictive control for lateral path tracking, IEEE Transactions on Intelligent Vehicles, 4, 4, 569-577.
11.
Menhour L., d’Andréa-Novel B., Fliess M., Mounier H., 2014, Coupled nonlinear vehicle control: Flatness-based setting with algebraic estimation techniques, Control Engineering Practice, 22, 135-146.
12.
Ortiz F.M., Sammarco M., Costa L.H.M., Detyniecki M., 2023, Applications and services using vehicular exteroceptive sensors: A survey, IEEE Transactions on Intelligent Vehicles, 8, 1, 949-969.
13.
Rokonuzzaman M., Mohajer N., Nahavandi S., Mohamed S., 2021, Model predictive control with learned vehicle dynamics for autonomous vehicle path tracking, IEEE Access, 9, 128233-128249.
15.
Sun Y.G., He Z.Y., Xu J.Q., Sun W., Lin G.B., 2023, Dynamic analysis and vibration control for a maglev vehicle-guideway coupling system with experimental verification, Mechanical Systems and Signal Processing, 188, 109954.
16.
Sun Y.G., Li F.X., Lin G.B., He Z.Y., 2023, Adaptive fault-tolerant control of high-speed maglev train suspension system with partial actuator failure: design and experiments, Journal of Zhejiang University-SCIENCE A, 24, 3, 272-283.
17.
Sun Y.G., Qiang H.Y., Wang L., Ji W., Mardani A., 2023, A fuzzy-logic-system-based cooperative control for the multielectromagnets suspension system of maglev trains with experimental verification, IEEE Transactions on Fuzzy Systems, 31, 10, 3411-3422.
18.
Sun Z.Y., Wang R.C., Meng X.P., Yang Y.Y., Wei Z.D., Ye Q., 2024, A novel path tracking system for autonomous vehicle based on model predictive control, Journal of Mechanical Science and Technology, 38, 1, 365-378.
19.
Wang R.R., Zhang H., Wang J.M., 2014, Linear parameter-varying controller design for four-wheel independently actuated electric ground vehicles with active steering systems, IEEE Transactions on Control Systems Technology, 22, 4, 1281-1296.
20.
Wang X., Sun W.C., 2023, Trajectory tracking of autonomous vehicle: A differential flatness approach with disturbance-observer-based control, IEEE Transactions on Intelligent Vehicles, 8, 2, 1368-1379.
21.
Wang Z.Q., Sun K.Y., Ma S.Q., Sun L.T., Gao W., Dong Z.Z., 2022, Improved linear quadratic regulator lateral path tracking approach based on a real-time updated algorithm with fuzzy control and cosine similarity for autonomous vehicles, Electronics, 11, 22, 3703.
22.
Xia Y.Q., Pu F., Li S.F., Gao Y., 2016, Lateral path tracking control of autonomous land vehicle based on ADRC and differential flatness, IEEE Transactions on Industrial Electronics, 63, 5, 3091-3099.
23.
Yang T., Bai Z.W., Li Z.Q., Feng N.L., Chen L.Q., 2021, Intelligent vehicle lateral control method based on feedforward + predictive LQR algorithm, Actuators, 10, 9, 228.
24.
Yu H.W., Zhang Z.Z., Xing J.F., 2021, Micro feed characteristic analysis of a new crawler guide rail dual drive servo system, Science Progress, 104, 3, 1-24.
25.
Zhuang Y.F., Ma G.F., Huang H.B., 2010, Time-optimal motion planning of an underactuated rigid spacecraft, Control and Decision (in Chinese), 25, 10, 1469-1473.
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| eISSN: | 2543-6309 |
| ISSN: | 1429-2955 |
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