Model predictive control design for polytopic uncertain systems by synthesising multi-step prediction scenarios

DOI10.1080/00207721.2017.1402214zbMath1385.93032OpenAlexW2770401837MaRDI QIDQ4638039

Yuli Xu, Dewei Li, Zhongxue Gan, Yu-Geng Xi, Jian-Bo Lu

Publication date: 3 May 2018

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2017.1402214

zbMATH Keywords

model predictive controlpolyhedral setsenlargement of feasible regionmaximal admissible setsmulti-step feedback control law

Mathematics Subject Classification ID

Control/observation systems with incomplete information (93C41) Discrete-time control/observation systems (93C55) Asymptotic stability in control theory (93D20)

Uses Software

• SDPT3
• YALMIP

Cites Work

• Robust constrained model predictive control using linear matrix inequalities
• Constrained robust model predictive control based on periodic invariance
• Decomposition principle in model predictive control for linear systems with bounded disturbances
• Theory and computation of disturbance invariant sets for discrete-time linear systems
• Implicit improved vertex control for uncertain, time-varying linear discrete-time systems with state and control constraints
• Computationally efficient algorithms for constraint handling with guaranteed stability and near optimality
• Interpolation methods in model predictive control: an overview
• Linear systems with state and control constraints: the theory and application of maximal output admissible sets
• SDPT3 — A Matlab software package for semidefinite programming, Version 1.3
• Interpolation based computationally efficient predictive control
• Interpolation techniques for robust constrained model predictive control based on polyhedral invariant set
• General interpolation in mpc and its advantages
• Constrained robust feedback model predictive control for uncertain systems with polytopic description

This page was built for publication: Model predictive control design for polytopic uncertain systems by synthesising multi-step prediction scenarios