Real-time model predictive control based on dual gradient projection: Theory and fixed-point FPGA implementation

Matteo Rubagotti, Panagiotis Patrinos, Alberto Guiggiani, Alberto Bemporad

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

This paper proposes a method to design robust model predictive control (MPC) laws for discrete-time linear systems with hard mixed constraints on states and inputs, in case of only an inexact solution of the associated quadratic program is available, because of real-time requirements. By using a recently proposed dual gradient-projection algorithm, it is proved that the discrepancy of the optimal control law as compared with the obtained one is bounded even if the solver is implemented in fixed-point arithmetic. By defining an alternative MPC problem with tightened constraints, a feasible solution is obtained for the original MPC problem, which guarantees recursive feasibility and asymptotic stability of the closed-loop system with respect to a set including the origin, also considering the presence of external disturbances. The proposed MPC law is implemented on a field-programmable gate array in order to show the practical applicability of the method.

Original languageEnglish
Pages (from-to)3292-3310
Number of pages19
JournalInternational Journal of Robust and Nonlinear Control
Volume26
Issue number15
DOIs
Publication statusPublished - Oct 1 2016

Keywords

  • model predictive control
  • optimization methods
  • uncertain systems

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Chemical Engineering(all)
  • Biomedical Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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