A Lie-bracket-based notion of stabilizing feedback in optimal control
Giovanni Fusco, Monica Motta, Franco Rampazzo

TL;DR
This paper explores a Lie-bracket-based framework for stabilizing feedback in optimal control, linking stabilizability, controllability, and cost regulation through the concept of Minimum Restraint Functions.
Contribution
It introduces a novel Lie-bracket-based notion of stabilizing feedback that incorporates iterated Lie brackets for cost regulation in control systems.
Findings
Asymptotic controllability is necessary for degree-k stabilizability.
The framework connects stabilizability with the existence of Minimum Restraint Functions.
Main results establish the link between stabilizability and controllability with cost regulation.
Abstract
For a control system two major issues can be considered: the stabilizability with respect to a given target, and the minimization of an integral functional (while the trajectories reach this target). Here we consider a problem where stabilizability or controllability are investigated together with the further aim of a "cost regulation", namely a state-dependent upper bounding of the functional. This paper is devoted to a crucial step in the program of establishing a chain of equivalences among degree-k stabilizability with regulated cost, asymptotic controllability with regulated cost, and the existence of a degree-k Minimum Restraint Function (which is a special kind of Control Lyapunov Function). Besides the presence of a cost we allow the stabilizing "feedback" to give rise to directions that range in the union of original directions and the family of iterated Lie bracket of length…
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Taxonomy
TopicsBiomedical and Chemical Research · Control and Stability of Dynamical Systems · Adaptive Control of Nonlinear Systems
