Model predictive control (MPC) is a popular controller design technique in the process industry. Conventional MPC uses linear or nonlinear discrete-time models. Recently, we have extended MPC to a class of discrete event systems that can be described by a model that is "linear" in the (max; +) algeb
β¦ LIBER β¦
Max-plus-linear model-based predictive control for constrained hybrid systems: linear programming solution
β Scribed by Yuanyuan Zou; Shaoyuan Li
- Publisher
- South China University of Technology and Academy of Mathematics and Systems Science, CAS
- Year
- 2007
- Tongue
- English
- Weight
- 134 KB
- Volume
- 5
- Category
- Article
- ISSN
- 1672-6340
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Model predictive control for perturbed m
β
T.J.J. van den Boom; B. De Schutter
π
Article
π
2002
π
Elsevier Science
π
English
β 165 KB
Stabilization of max-plus-linear systems
β
Ion Necoara; Ton J.J. van den Boom; Bart De Schutter; Hans Hellendoorn
π
Article
π
2008
π
Elsevier Science
π
English
β 314 KB
Max-plus-linear (MPL) systems are a class of event-driven nonlinear dynamic systems that can be described by models that are "linear" in the max-plus algebra. In this paper we derive a solution to a finite-horizon model predictive control (MPC) problem for MPL systems where the cost is designed to p
Dynamic programming for constrained opti
β
Francesco Borrelli; Mato BaotiΔ; Alberto Bemporad; Manfred Morari
π
Article
π
2005
π
Elsevier Science
π
English
β 305 KB
Adaptive model predictive control for a
β
Hiroaki Fukushima; Tae-Hyoung Kim; Toshiharu Sugie
π
Article
π
2007
π
Elsevier Science
π
English
β 240 KB
Costate prediction based optimal control
β
Minghui Hu; Yongshan Wang; Huihe Shao
π
Article
π
2008
π
Elsevier Science
π
English
β 471 KB