On efficient computation of low-complexity controlled invariant sets for uncertain linear systems

DOI10.1080/00207171003692662zbMath1200.93060OpenAlexW2170498251MaRDI QIDQ3161164

Bart De Moor, Mark Cannon, Toni Barjas Blanco

Publication date: 12 October 2010

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207171003692662

zbMATH Keywords

optimisationconstrained controlpolytopic invariant sets

Mathematics Subject Classification ID

Semidefinite programming (90C22) Control/observation systems with incomplete information (93C41) Linear systems in control theory (93C05)

Related Items (6)

Polyhedral estimates of the region of attraction of the origin of linear systems under aperiodic sampling and input saturation ⋮ Computation of robust control invariant sets with predefined complexity for uncertain systems ⋮ Tube‐enhanced multi‐stage model predictive control for flexible robust control of constrained linear systems with additive and parametric uncertainties ⋮ Computation of parameter dependent robust invariant sets for LPV models with guaranteed performance ⋮ Computation of low-complexity control-invariant sets for systems with uncertain parameter dependence ⋮ Construction of invariant polytopic sets with specified complexity

Cites Work

• Robust constrained model predictive control using linear matrix inequalities
• On the positive invariance of polyhedral sets for discrete-time systems
• A class of invariant regulators for the discrete-time linear constrained regulation problem
• Constrained control for uncertain linear systems
• Nonlinear model predictive control with polytopic invariant sets.
• Set invariance in control
• Extended invariance and its use in model predictive control
• Regulator problem for linear discrete-time systems with non-symmetrical constrained control
• Linear systems with state and control constraints: the theory and application of maximal output admissible sets
• Robust receding horizon predictive control for systems with uncertain dynamics and input saturation

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