Synthesis of constrained robust feedback policies and model predictive control

arXiv (Cornell University)

Abstract

In this work, we develop a method based on robust control techniques to synthesize robust time-varying state-feedback policies for finite, infinite, and receding horizon control problems subject to convex quadratic state and input constraints. To ensure constraint satisfaction of our policy, we employ (initial state)-to-peak gain techniques. Based on this idea, we formulate linear matrix inequality conditions, which are simultaneously convex in the parameters of an affine control policy, a Lyapunov function along the trajectory and multiplier variables for the uncertainties in a time-varying linear fractional transformation model. In our experiments this approach is less conservative than standard tube-based robust model predictive control methods.

Authors 4

1. Dennis Gramlich Aachen Intelligent Control Systems

   RWTH Aachen University

   Affiliation as printed

   Intelligent Control Systems , RWTH-Aachen , D- 52074 Aachen , Germany

2. Carsten W. Scherer Aachen Intelligent Control Systems

   University of Stuttgart · RWTH Aachen University

   Affiliation as printed

   Intelligent Control Systems , RWTH-Aachen , D- 52074 Aachen , Germany

   Mathematical Sys- tems Theory , University of Stuttgart , 70569 Stuttgart , Germany

3. Hannah Häring
4. Christian Ebenbauer Aachen Intelligent Control Systems

   RWTH Aachen University

   Affiliation as printed

   Intelligent Control Systems , RWTH-Aachen , D- 52074 Aachen , Germany