State-space approach to interpolation in MPC

DOI<link itemprop=identifier href="https://doi.org/10.1002/(SICI)1099-1239(200001)10:1<27::AID-RNC459>3.0.CO;2-5" /><27::AID-RNC459>3.0.CO;2-5 10.1002/(SICI)1099-1239(200001)10:1<27::AID-RNC459>3.0.CO;2-5zbMath0946.93018OpenAlexW2102639609MaRDI QIDQ4944620

Juan A. Medina Méndez, J. A. Rossiter, Basil Kouvaritakis

Publication date: 21 March 2000

Full work available at URL: https://doi.org/10.1002/(sici)1099-1239(200001)10:1<27::aid-rnc459>3.0.co;2-5

zbMATH Keywords

linear programminginterpolationsstate-space model predictive control

Mathematics Subject Classification ID

Linear programming (90C05) Design techniques (robust design, computer-aided design, etc.) (93B51)

Related Items (5)

Interpolation methods in model predictive control: an overview ⋮ Interpolation based computationally efficient 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

Cites Work

• A numerically robust state-space approach to stable-predictive control strategies
• Linear quadratic feasible predictive control
• Constrained linear quadratic regulation

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