Augmented Lagrangian Pattern Search Based Multi-Agent Model Predictive Control of Rhine-Meuse Delta

DOI10.1002/ASJC.1327zbMath1354.93052OpenAlexW2551000876MaRDI QIDQ2960148

No author found.

Publication date: 7 February 2017

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

Full work available at URL: https://doi.org/10.1002/asjc.1327

zbMATH Keywords

large scale systemsdistributed model predictive controlmulti-agent controlaugmented Lagrangian pattern search

Mathematics Subject Classification ID

Application models in control theory (93C95) Discrete-time control/observation systems (93C55) Decentralized systems (93A14) Large-scale systems (93A15) Agent technology and artificial intelligence (68T42)

Uses Software

• MultiMin

Cites Work

• Unnamed Item
• Unnamed Item
• Model predictive control. With a foreword by M. J. Grimble and M. A. Johnson
• Derivative-free optimization: a review of algorithms and comparison of software implementations
• On the Convergence of Pattern Search Algorithms
• A Globally Convergent Augmented Lagrangian Algorithm for Optimization with General Constraints and Simple Bounds
• Introduction to Derivative-Free Optimization
• On the Convergence of the Multidirectional Search Algorithm
• A Globally Convergent Augmented Lagrangian Pattern Search Algorithm for Optimization with General Constraints and Simple Bounds

This page was built for publication: Augmented Lagrangian Pattern Search Based Multi-Agent Model Predictive Control of Rhine-Meuse Delta