Decomposition principle in model predictive control for linear systems with bounded disturbances

DOI10.1016/j.automatica.2009.04.012zbMath1185.93024OpenAlexW1973928453MaRDI QIDQ963791

B. E. Eshmatov

Publication date: 14 April 2010

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2009.04.012

zbMATH Keywords

model predictive controldecomposition principlelinear constrained systems with bounded disturbances

Mathematics Subject Classification ID

Related Items (4)

Model predictive control design for polytopic uncertain systems by synthesising multi-step prediction scenarios ⋮ Variable structure disturbance rejection control for nonlinear uncertain systems with state and control delays via optimal sliding mode surface approach ⋮ Robust output feedback time optimal decomposed controllers for linear systems via moving horizon estimation ⋮ One-step ahead robust MPC for LPV model with bounded disturbance

Cites Work

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• Worst-case formulations of model predictive control for systems with bounded parameters
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• Efficient robust predictive control
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• Linear Matrix Inequalities in System and Control Theory
• Feedback min‐max model predictive control using a single linear program: robust stability and the explicit solution
• Min-max feedback model predictive control for constrained linear systems
• Interpolation based computationally efficient predictive control
• General interpolation in mpc and its advantages
• Optimizing prediction dynamics for robust MPC
• Systems with persistent disturbances: Predictive control with restricted constraints

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