Data-driven optimization framework for nonlinear model predictive control

DOI10.1155/2017/9402684zbMath1426.93093OpenAlexW2747143215MaRDI QIDQ1993318

Lixin Jia, Zonglin Ye, Xiali Hei, Shiliang Zhang, Hui Cao, Yan-Bin Zhang

Publication date: 5 November 2018

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2017/9402684

zbMATH Keywords

linearizationnonlinear model predictive controlhybrid-learning algorithm

Mathematics Subject Classification ID

Nonlinear systems in control theory (93C10) Linearizations (93B18) Model predictive control (93B45)

Uses Software

• ANFIS

Cites Work

• Unnamed Item
• Advanced control of industrial processes. Structures and algorithms.
• Generalized predictive control. I: The basic algorithm
• Artificial neural networks in process estimation and control
• Nonlinear model predictive control of a simulated multivariable polymerization reactor using second-order Volterra models
• A receding-horizon regulator for nonlinear systems and a neural approximation
• Non-linear generalized predictive control (NLGPC) applied to muscle relaxant anaesthesia
• A Family of Model Predictive Control Algorithms With Artificial Neural Networks

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