ZonoReach: A Reachability-Guided Controller Using Zonotopes and Local Hamilton–Jacobi Analysis

Journal Article (2025)
Author(s)

I.Z. El-Hajj (TU Delft - Control & Simulation)

J.J. van Beers (TU Delft - Aerospace Engineering)

P. Solanki (TU Delft - Control & Simulation)

Research Group
Control & Simulation
DOI related publication
https://doi.org/10.1007/s12555-025-0554-z
More Info
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Publication Year
2025
Language
English
Research Group
Control & Simulation
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. @en
Issue number
11
Volume number
23
Pages (from-to)
3199-3208
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Abstract

This paper presents a reachability-guided controller for nonlinear systems that synthesizes pseudo-optimal control using only local linear models. At each step, a forward reachable tube (FRT) is computed via zonotope-based set propagation; the closest point in the FRT to the target is chosen as an intermediate waypoint, around which a backward reachable tube (BRT) is solved using Hamilton–Jacobi (HJ) reachability. The resulting value function yields a locally optimal control action. This process is repeated iteratively to steer the system toward the target without requiring global nonlinear dynamics. We evaluate the method on the double integrator, inverted pendulum, and Dubins car, benchmarking against model predictive control baselines. For the double integrator, we additionally benchmark against its ground-truth time-optimal bang-bang solution. Our proposed ZonoReach controller achieves successful setpoint tracking and near time-optimal performance. Results highlight the influence of planning and control horizons, while limitations include reliance on local linear approximations and grid-based solvers for BRT computation. We conclude with directions for improving scalability toward real-world systems.

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