Set-Valued State Estimation for Nonlinear Systems Using Hybrid Zonotopes
- Resource Type
- Conference
- Authors
- Siefert, Jacob A.; Thompson, Andrew F.; Glunt, Jonah J.; Pangborn, Herschel C.
- Source
- 2023 62nd IEEE Conference on Decision and Control (CDC) Decision and Control (CDC), 2023 62nd IEEE Conference on. :2172-2177 Dec, 2023
- Subject
- Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Discrete-time systems
Uncertainty
System dynamics
Neural networks
Observers
Particle filters
Complexity theory
- Language
- ISSN
- 2576-2370
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.