Accelerating linear model predictive control by constraint removal

DOI10.1016/j.ejcon.2017.02.003zbMath1367.93201OpenAlexW2594895374MaRDI QIDQ2011973

Michael Jost, Gabriele Pannocchia, Martin Mönnigmann

Publication date: 27 July 2017

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

Full work available at URL: http://hdl.handle.net/11568/885106

zbMATH Keywords

quadratic programminglinear systemsmodel predictive controlconstrained control

Mathematics Subject Classification ID

Related Items (2)

Convex-lifting-based robust control design using the tunable robust invariant sets ⋮ Nonlinear model predictive control with aggregated constraints

Uses Software

• fast_mpc

Cites Work

• A novel approach to multiparametric quadratic programming
• Fast, large-scale model predictive control by partial enumeration
• Online constraint removal: accelerating MPC with a Lyapunov function
• A numerically robust state-space approach to stable-predictive control strategies
• An algorithm for multi-parametric quadratic programming and explicit MPC solutions
• Application of interior-point methods to model predictive control
• Constrained model predictive control: Stability and optimality
• Linear systems with state and control constraints: the theory and application of maximal output admissible sets
• Real-Time Suboptimal Model Predictive Control Using a Combination of Explicit MPC and Online Optimization
• Computational Complexity Certification for Real-Time MPC With Input Constraints Based on the Fast Gradient Method
• An online active set strategy to overcome the limitations of explicit MPC
• The explicit linear quadratic regulator for constrained systems

This page was built for publication: Accelerating linear model predictive control by constraint removal