Using interpolation to improve efficiency of multiparametric predictive control
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Publication:1776413
DOI10.1016/j.automatica.2004.08.021zbMath1061.93047OpenAlexW2067580637MaRDI QIDQ1776413
Publication date: 12 May 2005
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.automatica.2004.08.021
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Related Items (6)
Robust region elimination for piecewise affine control laws ⋮ A patchy approximation of explicit model predictive control ⋮ Using interpolation to improve efficiency of multiparametric predictive control ⋮ Long horizon input parameterisations to enlarge the region of attraction of MPC ⋮ Move blocked model predictive control with guaranteed stability and improved optimality using linear interpolation of base sequences ⋮ Alternative parameterisation within predictive control: a systematic selection
Cites Work
- Generalized predictive control. II: Extensions and interpretations
- Evaluation of piecewise affine control via binary search tree
- Suboptimal explicit receding horizon control via approximate multiparametric quadratic pro\-gramming
- Computation of the constrained infinite time linear quadratic regulator
- Using interpolation to improve efficiency of multiparametric predictive control
- Constrained model predictive control: Stability and optimality
- Computationally efficient algorithms for constraint handling with guaranteed stability and near optimality
- Efficient On-Line Computation of Constrained Optimal Control
- Linear systems with state and control constraints: the theory and application of maximal output admissible sets
- Constrained linear quadratic regulation
- Interpolation based computationally efficient predictive control
- State-space approach to interpolation in MPC
- Approximate explicit constrained linear model predictive control via orthogonal search tree
- The explicit linear quadratic regulator for constrained systems
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