Mathematical Method and Application of Machine Learning, 2nd Edition

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 624

Special Issue Editors


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Guest Editor
School of Mathematics and Statistics, Zhengzhou University, Zhenghzou 450052, China
Interests: network control systems; information physical systems; machine learning
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Mathematics and Statistics, Zhengzhou University, Zhengzhou 450001, China
Interests: delay differential equations; nonlinear time series analysis and predication; bifurcation; stability; chaos; synchronization; nonlinear dynamics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, artificial intelligence has rapidly entered the public field of vision and ushered in a period of rapid industrial development worldwide. As a component of artificial intelligence, machine learning is an important driving force of scientific research and the application of artificial intelligence and will bring a series of fundamental changes to traditional decision making. At present, machine learning is widely used in industrial and agricultural production, transportation, the military, and information technology, yielding many remarkable achievements. We are organizing this Special Issue to promote the cross-integration of machine learning, industrial production, and social life, and actively carry out interdisciplinary exploratory research and show the achievements of machine learning applications.

Prof. Dr. Xunlin Zhu
Prof. Dr. Lijun Pei
Guest Editors

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Keywords

  • machine learning 
  • artificial intelligence 
  • applied mathematics
  • machine learning applications

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Published Papers (1 paper)

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Research

17 pages, 1084 KiB  
Article
Design of Adaptive Finite-Time Backstepping Control for Shield Tunneling Systems with Constraints
by Kairong Hong, Lulu Yuan, Xunlin Zhu and Fengyuan Li
Mathematics 2024, 12(14), 2230; https://doi.org/10.3390/math12142230 - 17 Jul 2024
Viewed by 364
Abstract
This paper focuses on the finite-time tracking control problem of shield tunneling systems in the presence of constraints on the states and control input. By modeling the system based on the LuGre friction model, an effective method of tracking control in finite time [...] Read more.
This paper focuses on the finite-time tracking control problem of shield tunneling systems in the presence of constraints on the states and control input. By modeling the system based on the LuGre friction model, an effective method of tracking control in finite time is designed to overcome these actual constraints at the same time. First, the constraint on the system state is transformed into a symmetric constraint on the tracking error, and the constraint on control input is handled by designing an auxiliary differential equation. Then, radial basis function (RBF) neural networks are introduced to approximate the uncertainties. Next, using an adaptive finite-time backstepping method and choosing a logarithmic barrier Lyapunov function (BLF), a finite-time controller is designed to realize the finite-time stability of the closed-loop system. Finally, a simulation example is given to verify the correctness and validity of the theoretical results. Full article
(This article belongs to the Special Issue Mathematical Method and Application of Machine Learning, 2nd Edition)
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