CUED Publications database

Stability of model predictive control using Markov Chain Monte Carlo optimisation

Siva, E and Goulart, P and Maciejowski, J and Kantas, N (2014) Stability of model predictive control using Markov Chain Monte Carlo optimisation. In: UNSPECIFIED pp. 2851-2856..

Full text not available from this repository.

Abstract

© 2009 EUCA. We apply stochastic Lyapunov theory to perform stability analysis of MPC controllers for nonlinear deterministic systems where the underlying optimisation algorithm is based on Markov Chain Monte Carlo (MCMC) or other stochastic methods. We provide a set of assumptions and conditions required for employing the approximate value function obtained as a stochastic Lyapunov function, thereby providing almost sure closed loop stability. We demonstrate convergence of the system state to a target set on an example, in which simulated annealing with finite time stopping is used to control a nonlinear system with non-convex constraints.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Subjects: UNSPECIFIED
Divisions: Div F > Control
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:40
Last Modified: 03 Aug 2017 03:11
DOI: