仕訳帳情報
IET Control Theory & Applications
https://digital-library.theiet.org/content/journals/iet-cta
インパクト ・ ファクター:
2.200
出版社:
IET
ISSN:
1751-8644
閲覧:
16903
追跡:
0
論文募集
IET Control Theory & Applications is devoted to control systems in the broadest sense, covering new theoretical results and the applications of new and established control methods. Among the topics of interest are system modelling, identification and simulation, the analysis and design of control systems (including computer-aided design), and practical implementation. The scope encompasses technological, economic, physiological (biomedical) and other systems, including man-machine interfaces.

Most of the papers published deal with original work from industrial and government laboratories and universities, but subject reviews and tutorial expositions of current methods are welcomed. Correspondence discussing published papers is also welcomed.

Applications papers need not necessarily involve new theory. Papers which describe new realisations of established methods, or control techniques applied in a novel situation, or practical studies which compare various designs, would be of interest. Of particular value are theoretical papers which discuss the applicability of new work or applications which engender new theoretical applications.
最終更新 Dou Sun 2024-08-11
Special Issues
Special Issue on Adaptive Control Algorithms for Complex Dynamical Systems
提出日: 2024-12-31

In many industrial applications, the process parameters of many control systems are unknown or partially unknown. Due to these uncertainties and unknown factors, most practical industrial production processes cannot be described by simple deterministic models and would be quite difficult to control in practice. Therefore, adaptive controllers are considered as an important method to solve process uncertainty problems. Adaptive control scheme has attracted significant attention over the past few decades. It is known that the adaptive control model is a powerful tool for representing complex dynamical systems and many adaptive control methods have been successfully applied to the engineering field. Recently, many new results of modelling, control, and monitoring are developed in adaptive control systems, such as stochastic control, intelligent control, data-driven control and so on. We invite authors to contribute original research articles as well as review articles related to all aspects of modelling, control methods, optimization theories, monitoring, signal processing and fault detection for complex dynamical systems with adaptive control algorithms. All the submissions are expected to have original ideas and new approaches. Of particular interest are papers devoted to the development of engineering applications. Papers presenting computational issues, search strategies, and modelling and solution techniques to practical problems are also welcome. Topics for this call for papers include but not restricted to: Adaptive control and optimization of intelligent systems Adaptive learning control scheme Adaptive neural network modelling, control and optimization Adaptive fuzzy modelling, control and optimization Adaptive data driven modelling, control and optimization Adaptive Control and Signal Processing Adaptive estimation and fault detection algorithms Adaptive fault tolerant control and optimization Guest Editors: Shuping He Anhui University China Hai Wang Murdoch University Australia Edi Kurniawan National Research and Innovation Agency Indonesia
最終更新 Dou Sun 2024-08-11
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完全な名前インパクト ・ ファクター出版社
Journal of Research on Technology in Education4.500Taylor & Francis
Journal of Optical Communications and Networking4.000OSA Publishing
Bulletin of Electrical Engineering and InformaticsIAES
Optical Materials3.800Elsevier
Journal of Information Science and Engineering1.100Institute of Information Science
Open Systems and Information DynamicsSpringer
Egyptian Journal of Basic and Applied SciencesElsevier
International Journal for Numerical Methods in Fluids1.700Wiley-Blackwell
IEEE Intelligent Systems5.600IEEE
Natural Language Engineering2.500Cambridge University Press
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