Sensitivity-based multistep MPC for embedded systems

Titelangaben

Palma, Vryan Gil ; Suardi, Andrea ; Kerrigan, Eric C.:
Sensitivity-based multistep MPC for embedded systems.
Department of Mathematics, University of Bayreuth; Department of Electrical and Electronic Engineering, Imperial College London; Department of Electrical and Electronic Engineering and Department of Aeronautics, Imperial College London
Bayreuth , 2015 . - 6 S.

Volltext

Format: PDF Name: Palma_Suardi_Kerrigan_sensitivity-based_multistep_MPC_embedded_systems_nmpc_2015.pdf Version: Angenommene Version Verfügbar mit der Lizenz Deutsches Urheberrechtsgesetz. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt werden. Darüber hinaus bedürfen die Vervielfältigung, Bearbeitung, Verbreitung und jede Art der Verwertung der schriftlichen Zustimmung des jeweiligen Rechteinhabers.

Download (319kB)

Abstract

In model predictive control (MPC), an optimization problem is solved every sampling instant to determine an optimal control for a physical system. We aim to accelerate this procedure for fast systems applications and address the challenge of implementing the resulting MPC scheme on an embedded system with limited computing power. We present the sensitivity-based multistep MPC, a strategy which considerably reduces the computing requirements in terms of floating point operations (FLOPs), compared to a standard MPC formulation, while fulfilling closed-loop performance expectations. We illustrate by applying the method to a DC- DC converter model and show how a designer can optimally trade-off closed-loop performance considerations with computing requirements in order to fit the controller into a resource-constrained embedded system.