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Machines
Special Issues
Advanced Methodology of Intelligent Control and Measurement
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Advanced Methodology of Intelligent Control and Measurement

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 2098

Special Issue Editors

Prof. Dr. Wen-Jer Chang

E-Mail Website
Guest Editor
Department of Marine Engineering, National Taiwan Ocean University, Keelung 202, Taiwan
Interests: marine engineering; electrical engineering; system engineering; control engineering; intelligent control; fuzzy theory and control; multimedia application
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Cheung Chieh Ku

E-Mail Website
Guest Editor
Department of Marine Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 806, Taiwan
Interests: fuzzy control; lpv system; stochastic system; mixed performance control; marine engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Intelligent control and measurement based on fuzzy concepts, neural networks, switch technology, gain schedule, and learning methods have been widely discussed for practical applications such as autonomous systems, power systems, navigation, aerospace, robotics, boilers, and transportation systems for increasing capacities of automation. Additionally, it was applied for theorical developments about time-delay criteria, robust control mixed-performance issue, mean-square stability, observer-based problems, fault tolerance, and even-triggered control. With the above researched results, the quality and accuracy of intelligent control and measurement were substantially raised for attending the requirement of industrial engineering and automatic systems. According to the great calculation ability of computer, the intelligent control and measurement is thus still an interested issue for practical applications and theoretical developments to investigate stability issue and controller design methodology. The aim of this Special Issue on “Advanced Methodology of Intelligent Control and Measurement” is to explore and disseminate the novel ideas and research in control problems and signal measurement such as neural networks, fuzzy control, multi-agent control system, stochastic system, gain-scheduled control, large-scale system, switch control, observer-based control, predictive control, energy distribution, and polynomial system. Researchers and scholars in these domains are encouraged to submit their original, unpublished research. We welcome both research and review papers. Topics of interest that are invited for submission include, but are not limited to, the following:

  • Advanced methodologies of intelligent control
  • Applications of advances in intelligent control
  • Novel intelligent control method
  • Intelligent control improvement
  • Signal measurement
  • Optimal cost performance
  • Fault detection and diagnosis

Prof. Dr. Wen-Jer Chang
Prof. Dr. Cheung Chieh Ku
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • intelligent control
  • optimization
  • fuzzy logic
  • neural network
  • expert systems
  • system modeling and identification
  • sum-of-square
  • fault detection and toleration
  • power/energy system

Published Papers (2 papers)

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Research

20 pages, 2160 KiB  
Article
Constrained Cost Fuzzy Control via Decentralized Design Approach for Nonlinear Descriptor Interconnected Systems
by Wen-Jer Chang, Che-Lun Su, Cheung-Chieh Ku and Chein-Chung Sun
Machines 2023, 11(6), 666; https://doi.org/10.3390/machines11060666 - 20 Jun 2023
Viewed by 762
Abstract
This paper proposes a decentralized robust constrained cost fuzzy controller (DRCCFC) design for nonlinear descriptor interconnected systems (DIS) with uncertainties. The considered nonlinear DIS is modeled using Takagi–Sugeno fuzzy model (T-S FM) with fuzzy rules and strong interconnections. To derive sufficient stability conditions, [...] Read more.
This paper proposes a decentralized robust constrained cost fuzzy controller (DRCCFC) design for nonlinear descriptor interconnected systems (DIS) with uncertainties. The considered nonlinear DIS is modeled using Takagi–Sugeno fuzzy model (T-S FM) with fuzzy rules and strong interconnections. To derive sufficient stability conditions, the quadratic Lyapunov function (QLF) and free-weighting function (FWF) are defined. In contrast to the existing control approaches, the proportional–derivative feedback (PDF) control is introduced in this paper. Using the PDF control techniques, the regular and causal problems of the system can be solved easily. Based on the PDF control technique and constrained cost control (CCC) function, a set of fuzzy controllers are designed to effectively control the Takagi–Sugeno descriptor interconnected systems (T-S DIS). Then, the proposed sufficient conditions for the T-S DIS are derived in the form of linear matrix inequalities using the Schur complement technique. Finally, two simulation examples are provided to demonstrate the validity of the proposed control scheme. Full article
(This article belongs to the Special Issue Advanced Methodology of Intelligent Control and Measurement)
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23 pages, 980 KiB  
Article
Decentralized Adaptive Quantized Dynamic Surface Control for a Class of Flexible Hypersonic Flight Vehicles with Input Quantization
by Wenyan Zhao, Zeyu Lu, Zijian Bi, Cheng Zhong, Dianxiong Tian, Yanhui Zhang, Xiuyu Zhang and Guoqiang Zhu
Machines 2023, 11(6), 630; https://doi.org/10.3390/machines11060630 - 06 Jun 2023
Viewed by 781
Abstract
A control strategy for a certain class of hypersonic flight aircraft dynamic models with unknown parameters is proposed in this article. The strategy is adaptive dynamic surface input quantization control. To address the issues in conventional inversion control, a first-order low-pass filter and [...] Read more.
A control strategy for a certain class of hypersonic flight aircraft dynamic models with unknown parameters is proposed in this article. The strategy is adaptive dynamic surface input quantization control. To address the issues in conventional inversion control, a first-order low-pass filter and an adaptive parameter minimum learning law are introduced in the control system design process. This method has the following features: (1) it solves the problem of repeated differentiation of the virtual control law in the conventional back-stepping method, greatly simplifying the control law structure; (2) by using the norm of the neural network weight vector as the adaptive adjustment parameter instead of updating each element online, the number of adaptive adjustment parameters is significantly reduced, improving the execution efficiency of the controller; (3) the introduced hysteresis quantizer overcomes the disadvantage of the quantization accuracy deterioration when the input value is too low in the logarithm quantizer, improving the accuracy of the quantizer. Stability analysis has shown that all signals in the closed-loop system are semi-globally uniformly bounded, and simulation results have verified the effectiveness of the proposed adaptive quantized control scheme. Full article
(This article belongs to the Special Issue Advanced Methodology of Intelligent Control and Measurement)
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