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A Bilevel Programming Approach to the Convergence Analysis of Control-Lyapunov Functions
Author(s) -
Wentao Tang,
Pródromos Daoutidis
Publication year - 2019
Publication title -
ieee transactions on automatic control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.436
H-Index - 294
eISSN - 1558-2523
pISSN - 0018-9286
DOI - 10.1109/tac.2019.2892386
Subject(s) - lyapunov function , convexity , rate of convergence , mathematical optimization , mathematics , bilevel optimization , domain (mathematical analysis) , convergence (economics) , affine transformation , norm (philosophy) , lyapunov redesign , lyapunov equation , control theory (sociology) , nonlinear system , computer science , optimization problem , control (management) , artificial intelligence , channel (broadcasting) , law , economic growth , computer network , mathematical analysis , financial economics , quantum mechanics , political science , physics , pure mathematics , economics
This paper deals with the estimation of convergence rate and domain of attraction of control-Lyapunov functions in Lyapunov-based control. This pair of estimation problems has been considered only for input-affine systems with constraints on the input norm. In this paper, we propose a novel optimization framework to address the estimation of convergence rate and domain of attraction. Specifically, we formulate the estimation problems as min–max bilevel programs for the decay rate of the Lyapunov function, where the inner problem can be resolved using Karush–Kuhn–Tucker optimality conditions, and the resulting single-level programs can be transformed into and solved as mixed-integer nonlinear programs. The proposed approach is applicable to systems with input-nonaffinity or more general forms of input constraints under an input-convexity assumption.

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