Robust MPC suitable for closed-loop re-identification, based on probabilistic invariant sets

DOI10.1016/j.sysconle.2018.06.002zbMath1402.93094OpenAlexW2809072686MaRDI QIDQ1624904

Y. Aharonov

Publication date: 16 November 2018

Published in: Systems \& Control Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sysconle.2018.06.002

zbMATH Keywords

model predictive controlclosed-loop re-identificationprobabilistic invariant sets

Mathematics Subject Classification ID

Sensitivity (robustness) (93B35) System identification (93B30) Identification in stochastic control theory (93E12)

Related Items (3)

Self-triggered model predictive control for nonlinear continuous-time networked system via ensured performance control samples selection ⋮ Discrete-time MPC for switched systems with applications to biomedical problems ⋮ Probabilistic ultimate bounds and invariant sets in nonlinear systems

Cites Work

• Probabilistic set invariance and ultimate boundedness
• Min-max model predictive control of nonlinear systems: a unifying overview on stability
• Optimization over state feedback policies for robust control with constraints
• Efficient robust optimization for robust control with constraints
• Robust model predictive control using tubes.
• Robust model predictive control of constrained linear systems with bounded disturbances
• Model predictive control suitable for closed-loop re-identification
• Persistently exciting model predictive control
• Input-to-State Stability: A Unifying Framework for Robust Model Predictive Control
• Set-theoretic methods in control

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