Robust Safety Filtering for Input-Constrained Underactuated Linear Systems
Abstract
We present a robust safety-filtering framework for input-constrained underactuated linear systems subject to unknown disturbances. A baseline H-$\infty$ input is derived from a zero-sum differential game, while a disturbance observer supplies an estimate and a transient error bound. The baseline input is adjusted using the disturbance estimate, while the estimate and its error bound are used to define robust high-order control barrier function constraints; forward invariance holds as long as the...
Description / Details
We present a robust safety-filtering framework for input-constrained underactuated linear systems subject to unknown disturbances. A baseline H- input is derived from a zero-sum differential game, while a disturbance observer supplies an estimate and a transient error bound. The baseline input is adjusted using the disturbance estimate, while the estimate and its error bound are used to define robust high-order control barrier function constraints; forward invariance holds as long as the admissible-input set remains nonempty. For scalar-input systems, pointwise feasibility is determined from an exact input interval, and the interval width defines the feasibility margin. A finite-horizon H- performance balance accounts for the accumulated deviation of the applied input from the baseline H- policy. Simulations on a linearized two-wheeled balancing robot show how position and body-pitch constraints compete for the same bounded wheel-torque input.
Source: arXiv:2608.10872v1 - http://arxiv.org/abs/2608.10872v1 PDF: https://arxiv.org/pdf/2608.10872v1 Original Link: http://arxiv.org/abs/2608.10872v1
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Aug 12, 2026
Robotics
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