Synthesized AI LMI-based Criterion for Mechanical Systems
- Jcy Chen1,*, Wc Chen1, Tim Chen1, Alex Wilson2, N. Fadilah Jamaludin3, Nertrand Kapron1, Tim Chen4,5, John Burno5
1 Faculty of Information Technology, Ho Chi Minh City University, Ho Chi Minh City, Vietnam
2 Department of Data Science, RMIT University, Melbourne, VIC, Australia
3 School of Physical and Mathematical Technology, Nanyang Technological University, 21 Nanyang Link, Singapore, Singapore
4 Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
5 Heidelberg Academy of Sciences, Heidelberg, Baden-Württemberg, Germany
* Corresponding Author: Jcy Chen. Email:
, 
.
2 Department of Data Science, RMIT University, Melbourne, VIC, Australia
3 School of Physical and Mathematical Technology, Nanyang Technological University, 21 Nanyang Link, Singapore, Singapore
4 Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia
5 Heidelberg Academy of Sciences, Heidelberg, Baden-Württemberg, Germany
* Corresponding Author: Jcy Chen. Email:
Abstract
This paper proposes a novel artificial intelligence sythethized controller
in the mechanical system which has high speed computation because of the LMI
type criterion. The proposed membership functions are adopted and stabilization
criterion of the closed-loop T-S fuzzy systems are obtained through a new parametrized LMI (linear matrix) inequality which is rearranged by machine learning
membership functions.
Keywords
Fuzzy energy equation; artificial intelligence; large-scale systems; fuzzy model
Cite This Article
Chen, J., Chen, W., Chen, T., Wilson, A., Jamaludin, N. F. et al. (2019). Synthesized AI LMI-based Criterion for Mechanical Systems. Sound & Vibration, 53(6), 245–250.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.