2023 6th International Conference on Mechatronics and Computer Technology Engineering (MCTE 2023)

Keynote Speakers


Prof. Wei Yang

College of Mechanical and Vehicle Engineering, Chongqing University, China

Title: Research on Adaptive Neural Network H∞ Servo Control Method of Electronic Brake Booster

Abstract: Electronic Brake Booster (EBB) is a new type of executive structure of the Brake-By-Wire system applied to new energy vehicles. It is one of the important components of the Electro-Hydraulic Brake system (EHB) and plays an increasingly important role in brake energy recovery, advanced driving assistance, and other functions. Considering the EBB as the research object, an Adaptive Neural Network H∞ control strategy based on the H∞ control is proposed to approach the nonlinear part and the uncertain factors of the EBB system through the Radial Neural Network, in view of the situation that the fuzzy PID Three Loop control strategy will produce the current fluctuation and the moment impact under the emergency braking condition. The stability and convergence of the ANN-H∞ control strategy are proved in the sense of the Lyapunov Theory. Under the same condition as the Three Loop control strategy, the ANN-H∞ control strategy is modeled and simulated. The results are shown that the ANN-H∞ controller is superior to the Three Loop control strategy in the aspects of rapidity, static error, and stability. The simulation results of robustness verification show that the ANN-H∞ control strategy can still complete the EBB servo action in the absence of C-phase current, which significantly improves the anti-interference ability of the controller.

Experience: He is a professor, PhD, and doctoral supervisor in the College of Mechanical and Vehicle Engineering of Chongqing University. He is one of the "Double Innovation" talents in Jiangsu Province, a research mainstay of the "Changjiang Scholar and Innovation Team Development Program" of the Ministry of Education and the National Defense Science and Technology Innovation Team. He is an expert in the National Science and Technology Progress Award and the Science Progress Award of the Ministry of Education. He has long been engaged in the research of high-performance manufacturing technology and major equipment, new energy vehicles, and intelligent robots. He is responsible for or has conducted more than 50 scientific research projects entrusted by national, provincial, and ministerial levels and enterprises. He has received one first-class award, three second-class awards, and four third-class awards at the provincial and ministerial levels. He has published more than 100 papers in Mechanical Systems and Signal Processing, Proc. IMechE, Part K, IEEE TRANSACTIONS ON MAGNETICS,etc in important academic journals and international conferences. He has nearly 30 EI/SCI citing articles and has been granted more than 20 invention patents and software copyrights.

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Dr. Sailesh Iyer

Professor and  Dean, CSE/IT  Department, Rai  School  of  Engineering, India

Experience: Dr. Sailesh Iyer has a Ph.D. (Computer Science), pusruing Post Doc from University of Louisiana, Lafayette, USA (Public University ranked among the top 100 Public Universities) and currently serving as a Professor with Rai University, Ahmedabad. He has more than 23 years of experience in Academics, Industry and Corporate Training out of which 18 years are in core Academics. He has been awarded  Research Excellence Award for year 2021 by Rai University and an Honorary Adjunct Research Scientist at Neurolabs International under Dana Brain Health Institute, Iran from August 2022 to August 2025.  He has 2 Patents granted and one patent published to his credit and is involved as an Editor for various book projects with IGI Global (USA), CRC PressTaylor and Francis (UK) and Bentham Science (UAE). He has been invited as Keynote Speaker in various International Conferences held in China, Indonesia, Philippines, Saudi Arabia, Haiti, Ukraine, Italy and India. A hardcore Academician and Administrator, he has excelled in Corporate Training, Delivered 95+ Expert Talks in various AICTE sponsored STTP’s, ATAL FDP’s, Reputed Universities, Government organized Workshops, Orientation and Refresher Courses organized by HRDC, Gujarat University. Research Contribution include reputed Publications, Track Chair at ICDLAIR 2020 (Springer Italy), icSoftComp 2020, IEMIS 2020 (Springer), ICRITO 2020 (IEEE), ARISE-2021, FTSE-2021 and TPC Member of various reputed International and National Conferences, Reviewer of International Journals like Multimedia Tools and Applications (Springer), Journal of Computer Science (Scopus Indexed), International Journal of Big Data Analytics in Healthcare (IGI Global), Journal of Renewable Energy and Environment and Editor in various Journals. Expert Talk on Research based topics in various Universities and Conferences in addition to guiding Research Scholars as Supervisor. He has also been invited as a Judge for various events, Examiner for Reputed Universities, is a Computer Society of India Lifetime Member and also serving as Managing Committee (MC) Member, CSI Ahmedabad Chapter from 2018-2020.

Research interest areas:Computer Vision and Image Processing, Cyber Security, Data Mining and Analytics, Artificial Intelligence, Machine Learning, Blockchain.

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Prof. Yanguo Jing

Faculty of Business, Computing and Digital Industries, Leeds Trinity University, British

Experience: Professor Dr. Yanguo Jing is the Dean of the Faculty of Business, Computer Science and Digital Industries, Leeds Trinity University. He is a Professor of Artificial Intelligence. He has a PhD (Heriot-Watt University, UK), a MSc, a 1st class BSc (Hons) in Computer Science and a PGCert in Learning and Teaching in Higher Education. He has over 20 years’ teaching, research and enterprise experience in the UK and in China. Prof. Jing is a Fellow of the British Computer Society, a Charter IT professional and a Principal Fellow of the Higher Education Academy in the UK. Prof. Jing’s prime research interests are AI and big data. His recent research work focuses on the use of machine-learning methods to capture interaction and user behaviour patterns that can be used to develop intelligent applications. This research has been applied in applications such as business analytics, sports analytics, and user behaviour pattern recognition in social networks and extra-care/ Assisted Living settings. He participated in several research, KTP and consultancy projects with sponsors and clients such as Cadent Gas, Pfizer, Welsh Government, KPIT, UK’s Comic Relief charity and JISC in the UK. Prof. Jing has been instrumental in bringing over £30M funding in innovation and executive education.


Prof. Kejia Zhuang

Wuhan University of Technology, China

Experience: Kejia Zhuang obtained his PhD in Mechanical Science and Engineering on hig-ficiency machining of aeroengine turbine-used Inconel 718 alloy at Huazhong University of Science and Technology. He was recruited into the Hubei Digital Manufacturing Key Laboratory of Wuhan University of Technology (China). It was there that he founded a branch of his research team to carry on the topic related to cutting mechanism of dfclt-to-cut materials. During this period, he has undertaken some research projects. To broaden the research perspective, Kejia Zhuang had paid his visit to Lund University (Sweden) and Linkbping University (Sweden) in 2019-2020. He develops a systematic approach that incorporates classical cutting theories with finite element method (FEM) and itelligent algorithms. He also carries out fundamental researches on material flow characterization, multi-physics field modeling and micro-structure evolution, achieving ultimately the prediction and control of functional relability and surface integrity for critical parts. These studies have enabled him to (co-)author over 40 publications on internatinally famous journals like JMSE- JMSE, WEAR, JMPT and IJMS. These achievements have earmned him the title of communication review expert at National Natural Science Foundation of China and jourmal review expert for known joumals such as ASME-JMSE, WEAR and Proceedings of the British Mechanical Science Association.