AI & ML
Reach-Stabilize Control of Control-Affine Systems with Unknown Affine Parameters
arXiv eess.SY0 views
arXiv:2610.11900v1 Announce Type: cross Abstract: This paper considers the reach-stabilize prob- lem for a class of nonlinear control-affine systems with unknown parametric uncertainties, where the system states must remain in a safe set at all times, or enter a safe set in finite time and then remain in it, and converge to a goal point. An estimator is designed that generates a parameter estimate and a computable, nonincreasing bound on the estimation error from a known initial error bound, without requiring persistence of excitation. The bound defines margins that are added to a control barrier and a control Lyapunov function condition, which are then enforced in a quadratic program for efficient control design. It is shown that, for the closed-loop system, the safe set is forward invariant when the system starts within the safe set and is finite-time reachable from outside the safe set with a recovery-time bound that does not depend on the unknown parameter, and that the goal point is exponentially stable. In two numerical examples, with the initial state outside and inside the safe set, the proposed control policy, a baseline oracle control policy that uses the true parameter, both recover or remain in the safe set and converge to the goal point, while another baseline control policy that uses a fixed, incorrect, parameter does not remain
Source:https://arxiv.org/abs/2610.11900PreviousSpatiotemporal Response Decay for Near-Optimal Distributed LQR via System Level SynthesisNextCAPABLE: Capability-Aware Policy Adaptation via Behavioral Latent Encoding
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