Reducing Conservativeness of Polytopic Linear-Parameter-Varying Robust Vehicle Sideslip Angle Observer Through Minimum-Area Convex Quadrilateral Design

Conference · Sun Oct 01 00:00:00 EDT 2023

DOI:https://doi.org/10.1109/IAVVC57316.2023.10328147· OSTI ID:2267624

Zhou, Xingyu ^[1]; Ahn, Hyunjin ^[1]; Shen, Heran ^[2]; Kung, Yung-Chi ^[1]; Wang, Zejiang ^[3]; Wang, Junmin ^[1]

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1. The University of Texas at Austin
2. University of Texas at Austin
3. ORNL

The polytopic linear-parameter-varying (LPV) method has become increasingly popular for designing intelligent control and estimation systems for ground vehicles, particularly for the vehicle sideslip angle observer. In vehicle lateral dynamics, the vehicle longitudinal velocity-induced nonlinearities are conventionally outer-approximated with polytopes such as rectangles or triangles to obtain a polytopic LPV system. Yet, such polytopic approximations tend to be conservative and may lead to inadequate observer performance. To address this issue, a minimum-area convex quadrilateral construction is proposed in this paper to reduce design conservatism. The suggested design is demonstrated through the synthesis of an LPV H ∞ robust vehicle sideslip angle observer. Furthermore, a dSPACE-ASM simulation study is conducted to demonstrate the effectiveness and the advantage of the proposed polytopic construction over a baseline approach.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 2267624
• Resource Relation: Conference: 2023 IEEE International Automated Vehicle Validation Conference (IAVVC) - Austin, Texas, United States of America - 10/16/2023 4:00:00 AM-10/18/2023 4:00:00 AM
• Country of Publication: United States
• Language: English