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Fuzzy-Model-Based Robust Predictive Control for Path Tracking in Autonomous Driving

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Advances in Guidance, Navigation and Control ( ICGNC 2022)

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Abstract

This paper investigates the problem of path tracking for autonomous vehicles with parameter uncertainties and constraints. The dynamical model for the autonomous driving system is presented using fuzzy modeling techniques. Through online calculation, the robust positively invariant (RPI) set is determined, then an robust fuzzy model predictive controller is obtained. The system performance of the controller is computed by solving a series of constraints in terms of linear matrix inequalities. Finally, Carsim/Matlab co-simulation platform demonstrates the performance of the mentioned methodology.

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Authors and Affiliations

  1. Tongji University, Shanghai, China

    Jun Zhang, Changzhu Zhang, Zhuping Wang & Hao Zhang

Authors
  1. Jun Zhang
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  2. Changzhu Zhang
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  3. Zhuping Wang
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  4. Hao Zhang
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Corresponding author

Correspondence to Jun Zhang .

Editor information

Editors and Affiliations

  1. Ningbo Institute of Technology, Beihang University, Ningbo, China

    Liang Yan

  2. School of Automation Science and Electrical Engineering, Beihang University, Beijing, Beijing, China

    Haibin Duan

  3. School of Automation Science and Electrical Engineering, Beihang University, Beijing, Beijing, China

    Yimin Deng

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Zhang, J., Zhang, C., Wang, Z., Zhang, H. (2023). Fuzzy-Model-Based Robust Predictive Control for Path Tracking in Autonomous Driving. In: Yan, L., Duan, H., Deng, Y. (eds) Advances in Guidance, Navigation and Control. ICGNC 2022. Lecture Notes in Electrical Engineering, vol 845. Springer, Singapore. https://doi.org/10.1007/978-981-19-6613-2_684

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