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

Publication Type
Conference Paper
Book Title
2023 IEEE International Automated Vehicle Validation Conference (IAVVC)
Publication Date
Page Numbers
1 to 6
Publisher Location
New Jersey, United States of America
Conference Name
2023 IEEE International Automated Vehicle Validation Conference (IAVVC)
Conference Location
Austin, Texas, United States of America
Conference Sponsor
Conference Date

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.