Synthesis of constrained robust feedback policies and model predictive control

European Control Conference (ECC), pp. 3476–3483

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 Chair of Intelligent Control Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Intelligent Control Systems,Aachen,Germany,52074

2. Carsten W. Scherer

   University of Stuttgart

   Affiliation as printed

   University of Stuttgart,Chair of Mathematical Systems Theory,Stuttgart,Germany,70569

3. Hannah Häring Aachen Chair of Intelligent Control Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Intelligent Control Systems,Aachen,Germany,52074

4. Christian Ebenbauer Aachen Chair of Intelligent Control Systems

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Intelligent Control Systems,Aachen,Germany,52074