Set-valued State Estimation for Nonlinear Systems Using Hybrid Zonotopes

2023/04/17 by Jacob A. Siefert, Andrew F. Thompson, Siefert, Jacob A. +5 · 1 citation
Computer Science · Engineering · #Control Systems and Identification #FOS: Electrical engineering #Fault Detection and Control Systems #Neural Networks and Applications #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2304.07924

openalex publication_date 2023/04/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper proposes a method for set-valued state estimation of nonlinear, discrete-time systems. This is achieved by combining graphs of functions representing system dynamics and measurements with the hybrid zonotope set representation that can efficiently represent nonconvex and disjoint sets. Tight over-approximations of complex nonlinear functions are efficiently produced by leveraging special ordered sets and neural networks, which enable computation of set-valued state estimates that grow linearly in memory complexity with time. A numerical example demonstrates significant reduction of conservatism in the set-valued state estimates using the proposed method as compared to an idealized convex approach.

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