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Robust \(\mathcal {H}_\infty \) Path Following Control for Autonomous Ground Vehicles with Delay and Data Dropout

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Robust Gain-Scheduled Estimation and Control of Electrified Vehicles via LPV Technique

Part of the book series: Key Technologies on New Energy Vehicles ((KTNEV))

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Abstract

This chapter presents a robust \(\mathcal {H}_\infty \) path following control strategy for autonomous ground vehicles (AGV) with delays and data dropouts. The state measurements and signal transmissions usually suffer from inevitable delays and data packet dropouts, which may degrade the control performance or even deteriorate the system stability. A robust \(\mathcal {H}_\infty \) state-feedback controller is proposed to achieve the path following and vehicle lateral control simultaneously. A generalized delay representation is formulated to include the delays and data dropouts in the measurement and transmission. The uncertainties of the tire cornering stiffness and the external disturbances are also considered to enhance the robustness of the proposed controller. Two simulation cases are presented with a high-fidelity and full-car model based on the CarSim-Simulink joint platform, and the results verify the effectiveness and robustness of the proposed control approach.

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Acknowledgements

This chapter is from the previous work in [27], and some typos are corrected here.

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Authors and Affiliations

  1. Beihang University, Bei**g, China

    Hui Zhang

  2. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China

    Rongrong Wang

  3. The University of Texas at Austin, Austin, TX, USA

    Junmin Wang

Authors
  1. Hui Zhang
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  2. Rongrong Wang
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  3. Junmin Wang
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Correspondence to Rongrong Wang .

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Zhang, H., Wang, R., Wang, J. (2023). Robust \(\mathcal {H}_\infty \) Path Following Control for Autonomous Ground Vehicles with Delay and Data Dropout. In: Robust Gain-Scheduled Estimation and Control of Electrified Vehicles via LPV Technique. Key Technologies on New Energy Vehicles. Springer, Singapore. https://doi.org/10.1007/978-981-19-8509-6_6

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  • DOI: https://doi.org/10.1007/978-981-19-8509-6_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-8508-9

  • Online ISBN: 978-981-19-8509-6

  • eBook Packages: EngineeringEngineering (R0)

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