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» Nonlinear predictive control based on neural multi-models
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AUTOMATICA
2005
108views more  AUTOMATICA 2005»
14 years 9 months ago
Enlarging the domain of attraction of MPC controllers
This paper presents a method for enlarging the domain of attraction of nonlinear model predictive control (MPC). The usual way of guaranteeing stability of nonlinear MPC is to add...
Daniel Limón, T. Alamo, Eduardo F. Camacho
ICONIP
2008
14 years 11 months ago
The Diversity of Regression Ensembles Combining Bagging and Random Subspace Method
Abstract. The concept of Ensemble Learning has been shown to increase predictive power over single base learners. Given the bias-variancecovariance decomposition, diversity is char...
Alexandra Scherbart, Tim W. Nattkemper
ASIAMS
2008
IEEE
15 years 4 months ago
HiNFRA: Hierarchical Neuro-Fuzzy Learning for Online Risk Assessment
Our previous research illustrated the design of fuzzy logic based online risk assessment for Distributed Intrusion Prediction and Prevention Systems (DIPPS) [3]. Based on the DIPP...
Kjetil Haslum, Ajith Abraham, Svein J. Knapskog
CDC
2010
IEEE
163views Control Systems» more  CDC 2010»
14 years 5 months ago
Integrated dynamic optimization and control in reservoir engineering using locally identified linear models
Abstract-- Studies on dynamic real-time optimization (DRTO) of waterflooding strategies in petroleum reservoirs have demonstrated that there exists a large potential to improve eco...
Gijs van Essen, Amin Rezapour, Paul M. J. Van den ...
GECCO
2003
Springer
100views Optimization» more  GECCO 2003»
15 years 3 months ago
Active Guidance for a Finless Rocket Using Neuroevolution
Finless rockets are more efficient than finned designs, but are too unstable to fly unassisted. These rockets require an active guidance system to control their orientation durin...
Faustino J. Gomez, Risto Miikkulainen