Data-Driven Adaptive Predictive Control Method With Autotuned Weighting Factor for Nonlinear Systems Using Triangular Dynamic Linearization-Reference-Cited by-同舟云学术

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Data-Driven Adaptive Predictive Control Method With Autotuned Weighting Factor for Nonlinear Systems Using Triangular Dynamic Linearization

Published:2024-08 Issue:8 Volume:11 Page:1880-1882
ISSN:2329-9266
Container-title:IEEE/CAA Journal of Automatica Sinica
language:
Short-container-title:IEEE/CAA J. Autom. Sinica

Author:

Pang Zhong-Hua¹^ORCID,Zhang Yumo¹^ORCID,Sun Xueyuan²^ORCID,Gao Shengnan¹,Liu Guo-Ping³^ORCID

Affiliation:

1. North China University of Technology,Key Laboratory of Fieldbus Technology and Automation of Beijing,Beijing,China,100144

2. School of Data Science, Capital University of Economics and Business,Beijing,China,100070

3. Center for Control Science and Technology, Southern University of Science and Technology,Shenzhen,China,518055

Funder

National Natural Science Foundation of China

Beijing Natural Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6570654/10605755/10605732.pdf?arnumber=10605732

Reference10 articles.

1. Mpc-based motion planning and control enables smarter and safer autonomous marine vehicles: perspectives and a tutorial survey

2. Optimization-Based Estimation and Model Predictive Control for High Performance, Low Cost Software-Defined Power Electronics

3. Observer-Based Incremental Predictive Control of Networked Multi-Agent Systems With Random Delays and Packet Dropouts

4. Comparison of Three Data-Driven Networked Predictive Control Methods for a Class of Nonlinear Systems

5. Data-Driven Model Predictive Control With Stability and Robustness Guarantees

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