Notice of retraction
Vol. 32, No. 8(2), S&M2292

ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

Instructions to authors
English    日本語

Instructions for manuscript preparation
English    日本語

Template
English

Publisher
 MYU K.K.
 Sensors and Materials
 1-23-3-303 Sendagi,
 Bunkyo-ku, Tokyo 113-0022, Japan
 Tel: 81-3-3827-8549
 Fax: 81-3-3827-8547

MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.


MYU Research

(proofreading and recording)


MYU K.K.
(translation service)


The Art of Writing Scientific Papers

(How to write scientific papers)
(Japanese Only)

Copyright(C) MYU K.K.
S&M2465 Research Paper of Special Issue

Research on Application of Optimized Sliding Mode Control Strategy in Ship Electric Energy Conversion Process

Su Zhen, Luan Rongyu, Zhang Cheng, Wang Fei, Zhang Xiyuan, Yang Yifei, and Fu Jingqi

(Received July 6, 2020; Accepted December 9, 2020)

Keywords: energy conversion, RBF neural network, sliding mode control, shore power technology, grid-connected, power supply stability, voltage sensor

To remedy the defects of the poor power grid connection and its poor stability at ports, we adopt a control strategy based on radial basis function (RBF) neural network adaptive sliding mode control. In addition, the sliding mode control is optimized by using a proportional–integral (PI) sliding surface and following a fractional sliding mode law. The neural network gives a general approximation: the parameter error is approximated by the neural network to compensate errors. Due to the good anti-interference and robustness of sliding mode control, the stability of the shore-to-ship power grid connection is improved. The sliding mode law is proved to be able to ensure the stability of the system when an RBF neural network is adopted to approximate errors. In the environment of a MATLAB simulation, a simulation model of a shore-to-ship power grid connection is built. A simulation experiment is performed under a low voltage of 440 V, and the simulation results at different frequencies are compared with the sliding mode control and proportional–integral–derivative (PID) results without an RBF neural network. As revealed by the results, the control strategy is effective and feasible.

Corresponding author: Fu Jingqi




Forthcoming Regular Issues


Forthcoming Special Issues

Special issue on Novel Materials and Sensing Technologies on Electronic and Mechanical Devices (2)-1
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Hsien-Wei Tseng (Longyan University)


Special Issue on Materials, Devices, Circuits, and Analytical Methods for Various Sensors (4)
Guest editor, Chien-Jung Huang (National University of Kaohsiung), Cheng-Hsing Hsu (National United University), Ja-Hao Chen (Feng Chia University), and Wei-Ling Hsu (Huaiyin Normal University)
Conference website


Special issue on Novel Materials and Sensing Technologies on Electronic and Mechanical Devices (2)-2
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Hsien-Wei Tseng (Longyan University)


Special Issue on New Trends in Robots and Their Applications
Guest editor, Ikuo Yamamoto (Nagasaki University)


Special Issue on Artificial Intelligence in Sensing Technologies and Systems
Guest editor, Prof. Lin Lin (Dalian University of Technology)
Call for paper


Special issue on Novel Materials and Sensing Technologies on Electronic and Mechanical Devices (3)
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Hsien-Wei Tseng (Longyan University)


Copyright(C) MYU K.K. All Rights Reserved.