- About IWCEAA 2024 -

What is the Latest in Control Engineering？

The 2024 8th International Workshop on Control Engineering and Advanced Algorithms （IWCEAA 2024） will be held on November 1-3 2024 in Nanjing China. IWCEAA 2024 is to bring together innovative academics and industrial experts in the field of Advanced Algorithms and Control Engineering to a common forum. The primary goal of the conference is to promote research and developmental activities in Advanced Algorithms and Control Engineering and another goal is to promote scientific information interchange between researchers developers engineers students and participant working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in Algorithms and Control Engineering and related areas.

Control Engineering: Now and in the Future Planned highlights of IWCEAA 2023 include:

● Addresses and presentations by some of the most respected researchers in the Advanced Algorithms and Control Engineering

● Panel discussions

● Presentations of accepted academic and practitioner research papers; a poster paper session

IMPORTANT DATES

Full Paper Submission Date

September 27 2024

Registration Deadline

October 10 2024

Final Paper Submission Date

October 20 2024

Conference Dates

November 1-3 2024

SPEAKERS

Prof. Simon X. Yang

University of Guelph CanadaProf. Simon X. Yang received the B.Sc. degree in engineering physics from Beijing University China in 1987 the first of two M.Sc. degrees in biophysics from Chinese Academy of Sciences Beijing China in 1990 the second M.Sc. degree in electrical engineering from the University of Houston USA in 1996 and the Ph.D. degree in electrical and computer engineering from the University of Alberta Edmonton Canada in 1999. Prof. Yang joined the School of Engineering at the University of Guelph Canada in 1999. Currently he is a Professor and the Head of the Advanced Robotics & Intelligent Systems （ARIS） Laboratory at the University of Guelph in Canada.

Prof. Yang has diversified research expertise. His research interests include intelligent systems robotics control systems sensors and multi-sensor fusion wireless sensor networks intelligent communications intelligent transportation machine learning and computational neuroscience. He has published over 600 academic papers including over 350 journal papers. Prof. Yang he has been very active in professional activities. He serves as the Editor-in-Chief of Intelligence & Robotics and International Journal of Robotics and Automation; and an Associate Editor of IEEE Transactions on Cybernetics IEEE Transactions on Artificial Intelligence and several other journals. He has been involved in the organization of many international conferences.

title：Bio-inspired Intelligent Control of Autonomous Underwater Vehicles

Abstract：Intelligent control of autonomous underwater vehicles （AUVs） are essentially important for many important applications such as security surveillance environmental monitoring and exploration in rivers lakes and seas particularly in unstructured hazardous and complex environments. In this talk a bio-inspired neural network system is first developed for real-time AUV path planning with the effect of dynamic currents and unpredictable obstacles by integrating a velocity synthesis algorithm. Then the bio-inspired neural network is extended to dynamic task assignment and path planning in a multi-AUV system where optimal results are obtained through a priority list derived by path distances deducted based on the neural network. After that efficient and robust trajectory tracking control of AUV without actuator saturation is developed based on fuzzy logic considering the environmental noise. Finally consensus formation tracking control of multi-AUV systems is developed using distributed bioinspired sliding mode control with guaranteed Lyapunov stability and smooth torque inputs. Extensive simulation experiments have verified the effectiveness and efficiency of the developed intelligent methods in applications to specific AUV systems with comparisons to existing mainstream methodologies.

Prof. Chun-Yi Su

Concordia University Canada

Dr. Chun-Yi Su received his Ph.D. degrees in control engineering from South China University of Technology in 1990. After a seven-year stint at the University of Victoria he joined the Concordia University in 1998 where he is currently a Professor of Mechanical and Industrial Engineering and Honorary Concordia University Research Chair. His research covers control theory and its applications to various mechanical systems with a focus on control of systems involving hysteresis nonlinearities. He is the author or co-author of over 500 publications which have appeared in journals as book chapters and in conference proceedings. He has been identified as Highly Cited Researchers from Clarivate since 2019.

Dr. Su has served as Associate Editor for several journals including IEEE Transactions on Automatic Control IEEE Transactions on Control Systems Technology IEEE Transactions on Cybernetics and several other journals. He is a Distinguished Lecturer of IEEE RA Society. He served for many conferences as an Organizing Committee Member including the General Chairs and Program Chairs.

Prof. Ning Sun

Nankai University ChinaNing Sun received the B.S. degree in measurement & control technology and instruments （with honors） from Wuhan University Wuhan China in 2009 and the Ph.D. degree in control theory and control engineering （with honors） from Nankai University Tianjin China in 2014. He is a Senior Member of the IEEE. He is currently a Professor with the Institute of Robotics and Automatic Information Systems Nankai University Tianjin China. His research interests include intelligent control for mechatronic/robotic systems with an emphasis on （industrial） applications.

Dr. Sun received the Machines 2021 Young Investigator Award the prestigious Japan Society for the Promotion of Science （JSPS） Postdoctoral Fellowship for Research in Japan （Standard） the Wu Wenjun Artificial Intelligence Excellent Youth Award in 2019 the ICCAR 2022 Young Scientist Award the China 10 Scientific and Technological Developments in Intelligent Manufacturing of 2019 several outstanding journal/conference paper awards etc. He serves as an Associate Editor for several journals including IEEE Transactions on Industrial Electronics IEEE Transactions on Systems Man and Cybernetics: Systems IEEE Transactions on Intelligent Transportation Systems IEEE Systems Journal and Journal of Field Robotics. In addition he has been an Associate Editor of the IEEE CSS Conference Editorial Board since July 2019 and he is/was an Associate Editor for the top robotics conferences IEEE ICRA and IEEE/RSJ IROS.

title: Intelligent Transportation Control for Underactuated Crane Systems With Applications

Abstract: As heavy industrial engineering machines cranes have been playing very important roles in various fields such as logistics construction metallurgy and manufacturing among others. The major task for cranes is to transport cargos from their initial positions to desired locations rapidly and accurately with negligible swing. At present most cranes used in practice are manipulated by human operators which exhibits such drawbacks as low efficiency poor anti-swing performance incorrect operations and high risks. Therefore the problem of anti-swing positioning control for cranes important both theoretically and practically. Cranes are typically underactuated systems i.e. they have fewer control inputs than their degrees of freedom （DoFs） making their control problem challenging. In this presentation I will first share some of our recent results on dynamics analysis motion planning and intelligent control of different crane systems including overhead cranes rotary cranes tower cranes ship-mounted cranes etc. with hardware experiments and applications. Then some of our extended and related researches on robotic systems with similar dynamic characteristics will also be discussed briefly including self-balance robots pneumatic artificial muscle （PAM）-actuated robots metal ingot polishing-oriented industrial robots and so on.

Prof. Zehui Mao

Nanjing University of Aeronautics and Astronautics China

Zehui Mao （Member IEEE） received the Ph.D. degree in control theory and control engineering from the Nanjing University of Aeronautics and Astronautics Nanjing China in 2009.She is currently a Professor with the College of Automation Engineering Nanjing University of Aeronautics and Astronautics. She was a Visiting Scholar with the University of Virginia Charlottesville VA USA. She worked in the areas of fault diagnosis with particular interests in nonlinear control systems sampled-data systems and networked control systems. Her current research interests include fault diagnosis and fault-tolerant control of systems with disturbance and incipient faults and high-speed train and spacecraft flight control applications.

Prof. Yajun Liu

South China University of Technology China

Prof. Yajun Liu was born on September 20 1974 in Jiangxi China. Native speaker of Chinese fluent in English. His Education and Academic Research Experiences is as follows: December 2016- Now Professor in South China University of Technology School of Mechanical and Automotive Engineering. December 2009- December 2010. Visiting Professor in Fluid Power Research Center （FPRC） Purdue University at West Lafayette USA. Feb 2005 – July 2016. Post-doctoral Research Fellow Tokheim JV company in China. June 2002 Ph. D. in Mechanical Engineering. South China University of Technology GuangzhouChina.

His research interests include Digital signal processing technology and its application in mechanical systems （such as hydraulic System for Energy Saving.）; Intelligence control and Manufacturing Engineering. Moreover Prof. Yajun Liu has published more than 270 papers in Journals and proceedings of international conferences. 40+ patents on Mechanical System design and manufacturing. My tentative title of presentation：signal processing method for Coriolis mass flowmeter based on deep learning.

title：An Intelligent Fire Detection Technology based on Acceleration Signal and Machine Learning

Abstract：Fire is a common and destructive disaster in modern society and traditional fire detection methods have limitations in terms of accuracy and speed. In this study an artificial intelligence-based fire detection technique is proposed which utilizes the vibration features of fireproof materials during combustion. Signal processing techniques such as time-domain analysis and wavelet packet decomposition are used to analyze the acceleration signals generated during burning and identify unique features that distinguish fire signals from other disturbances. Machine learning algorithms are then applied to train the feature data and perform parameter tuning to optimize the detection performance. The effectiveness of the method is validated through simulated fire experiments demonstrating that the technique can detect actual fire signals more quickly and accurately than traditional methods. This proposed method provides a new perspective for fire detection technology and has the potential to minimize the damage caused by fires.

- CALL FOR PAPERS -

The topics of interest for submission include but are not limited to:

Topics

* Algorithms and Data Structures

* Artificial Intelligence

* Electrical Systems

* Machine Learning Intelligent Data Analysis and Data Mining

* Mathematical and Computer Simulation

* Systems and Automation

* Process Control

* Network and System Integration

* Computer Control System

* Automatic Test and Fault Diagnosis

* Industrial Control Technology

PUBLICATION

Submit to Conference Proceedings （EI）

All accepted full papers will be published in IEEE and will be submitted to EI Compendex / Scopus  for indexing.

Note: All submitted articles should report original research results experimental or theoretical not previously published or under consideration for publication elsewhere. Articles submitted to the conference should meet these criteria. We firmly believe that ethical conduct is the most essential virtue of any academics. Hence any act of plagiarism or other misconduct is totally unacceptable and cannot be tolerated.