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Sparse Spectrahedral Shadows for State Estimation and Reachability Analysis: Set Operations, Validations and Order Reductions

2025-02-26 · Chengrui Wang, Haohao Qiu, Sibo Yao, James Lam

Set representations are the foundation of various set-based approaches in state estimation, reachability analysis and fault diagnosis. In this paper, we investigate spectrahedral shadows, a class of nonlinear geometric objects previously studied in semidefinite programming and real algebraic geometry. We demonstrate spectrahedral shadows generalize traditional and emerging set representations like ellipsoids, zonotopes, constrained zonotopes and ellipsotopes. Analytical forms of set operations are provided including linear map, linear inverse map, Minkowski sum, intersection, Cartesian product, Minkowski-Firey Lp sum, convex hull, conic hull and polytopic map, all of which are implemented without approximation in polynomial time. In addition, we develop set validation and order reduction techniques for spectrahedral shadows, thereby establishing spectrahedral shadows as a set representation applicable to a range of set-based tasks.

📄 PDF Abstract BibTeX arXiv:2502.18941

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Tasks

Fault DiagnosisState Estimation

Methods 이 논문이 사용한 방법론

SET Dynamic Sparse Training method where weight mask is updated randomly periodically

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