Model-Free Robust Backstepping Adaptive Cruise Control
This paper studies the model-free robust adaptive cruise control problem of a vehicle with unknown nonlinear dynamics and disturbances. First, under backstepping control framework, the position tracking errors with different spacing strategies are used to design a virtual control law, which provides...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2023/8839650 |
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| _version_ | 1849412640463388672 |
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| author | Yanan Zhang Jiacheng Song |
| author_facet | Yanan Zhang Jiacheng Song |
| author_sort | Yanan Zhang |
| collection | DOAJ |
| description | This paper studies the model-free robust adaptive cruise control problem of a vehicle with unknown nonlinear dynamics and disturbances. First, under backstepping control framework, the position tracking errors with different spacing strategies are used to design a virtual control law, which provides a velocity reference. Then, a novel data-driven sliding surface whose parameters are updated by designing estimation algorithm is developed to handle the unknown uncertainties and disturbances. Finally, the model-free robust backstepping adaptive cruise control (MFRB-ACC) method including PI control, model-free control, and robust control is designed. The novelty of the proposed control technique lies in its strong robustness, which is not based on the precise vehicle model. The designed data-driven sliding surface releases the necessity for the accurate mathematical model of the vehicle and guarantees the inherent robustness of the controller, in particular to uncertainties, modelling error, or external disturbance. Moreover, the designed controller contains three terms such that it has an effective decoupling ability and strong robustness. The effectiveness and superiority of the designed MFRB-ACC method are validated on MATLAB, and the simulation results show that compared to the PID algorithm, the designed MFRB-ACC algorithm can track its preceding vehicle with lower tracking error under different spacing strategies, different operating conditions, and low sampling frequencies. Especially at a sampling frequency of 0.1 s, the error under the PID-ACC increases from 0.2 m at a sampling frequency of 0.01 s to 2 m, and the error under MFRB-ACC has little change compared to the error at a sampling frequency of 0.01 s. |
| format | Article |
| id | doaj-art-5f7aeeb1ac264377b727cbc156f93eeb |
| institution | Kabale University |
| issn | 1687-5974 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-5f7aeeb1ac264377b727cbc156f93eeb2025-08-20T03:34:22ZengWileyInternational Journal of Aerospace Engineering1687-59742023-01-01202310.1155/2023/8839650Model-Free Robust Backstepping Adaptive Cruise ControlYanan Zhang0Jiacheng Song1School of Electronic and Control EngineeringCollege of Mechanical and Electronic EngineeringThis paper studies the model-free robust adaptive cruise control problem of a vehicle with unknown nonlinear dynamics and disturbances. First, under backstepping control framework, the position tracking errors with different spacing strategies are used to design a virtual control law, which provides a velocity reference. Then, a novel data-driven sliding surface whose parameters are updated by designing estimation algorithm is developed to handle the unknown uncertainties and disturbances. Finally, the model-free robust backstepping adaptive cruise control (MFRB-ACC) method including PI control, model-free control, and robust control is designed. The novelty of the proposed control technique lies in its strong robustness, which is not based on the precise vehicle model. The designed data-driven sliding surface releases the necessity for the accurate mathematical model of the vehicle and guarantees the inherent robustness of the controller, in particular to uncertainties, modelling error, or external disturbance. Moreover, the designed controller contains three terms such that it has an effective decoupling ability and strong robustness. The effectiveness and superiority of the designed MFRB-ACC method are validated on MATLAB, and the simulation results show that compared to the PID algorithm, the designed MFRB-ACC algorithm can track its preceding vehicle with lower tracking error under different spacing strategies, different operating conditions, and low sampling frequencies. Especially at a sampling frequency of 0.1 s, the error under the PID-ACC increases from 0.2 m at a sampling frequency of 0.01 s to 2 m, and the error under MFRB-ACC has little change compared to the error at a sampling frequency of 0.01 s.http://dx.doi.org/10.1155/2023/8839650 |
| spellingShingle | Yanan Zhang Jiacheng Song Model-Free Robust Backstepping Adaptive Cruise Control International Journal of Aerospace Engineering |
| title | Model-Free Robust Backstepping Adaptive Cruise Control |
| title_full | Model-Free Robust Backstepping Adaptive Cruise Control |
| title_fullStr | Model-Free Robust Backstepping Adaptive Cruise Control |
| title_full_unstemmed | Model-Free Robust Backstepping Adaptive Cruise Control |
| title_short | Model-Free Robust Backstepping Adaptive Cruise Control |
| title_sort | model free robust backstepping adaptive cruise control |
| url | http://dx.doi.org/10.1155/2023/8839650 |
| work_keys_str_mv | AT yananzhang modelfreerobustbacksteppingadaptivecruisecontrol AT jiachengsong modelfreerobustbacksteppingadaptivecruisecontrol |