Ming Zhang

Research Associate, PhD
Department of Naval Architecture, Ocean & Marine Engineering
Univerisity of Strathclyde
Email: ming.zhang.100@strath.ac.uk

Research Interests

Wave Energy Converter Hydrodynamics

Offshore Energy Farm

Wave Energy Converter

Power Absorption Improvement of WEC with MPC Control

Offshore Energy Farm

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Ship Manoeuvring

ship manoeuvring

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Obstacle avoidance decision making

ship manoeuvring

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Real-Time Control

Central control room

MRS autonomous ship

Model Predictive Control

Central control room

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Machine Learning

Artificial Intelligence

Long Short-term Momery Recurrent Neural Network

Theoretical PRediction Zone

Artificial Intelligence

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Offshore Green Hydrogen

MH2 offshore with logo

case study

MH2 offshore with logo

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Education Background:

Sep 2018 - Sep 2022: Ph.D. researcher in Naval Architecture, Ocean and Marine Engineering Department, University of Strathclyde, UK.
Sep 2011 - Mar 2018: MSc, BSc in Structure Design and Construction of Naval Architecture and Ocean Engineering Department, Harbin Engineering University.

Employment Background:

Octo 2022 - Present: Research Associate at University of Strathclyde, Glasgow, UK.
Sep 2021 - Sep 2022: Research Assistant at University of Strathclyde, Glasgow, UK.
Mar 2020 - Mar 2021: Teaching Assistant at University of Strathclyde (NM436 Dynamics of Offshore Structure; NM423 Seakeeping and Manoeuvring; NM325 Offshore Oil and Gas Production Systems).

Publication:

Zhang, M., Hao, S., Wu, D., Chen, M-L., & Yuan, Z-M. (2022). Time-optimal obstacle avoidance of autonomous ship based on nonlinear model predictive control. Ocean Engineering, 266(Part 1), [112591]. https://doi.org/10.1016/j.oceaneng.2022.112591.
Hu L., Zhang M.*, et al. Real-time control of ship's roll motion with gyrostabilisers, Ocean Engineering, 2023.
Hu L., Zhang M.*, et al. Predictive Control of a Heaving Compensation System Based on Machine Learning Prediction Algorithm, Journal of Marine Science and Engineering, 2023.
Zhang M., et al. LSTM RNN-based Excitation Force Prediction for The Real-time Control of Wave Energy Converters, Ocean Engineering, 2023.
Huo, F., Zhao, Y., Zhang, J., Zhang, M., & Yuan, Z. M. (2023). Study on wave slamming characteristics of a typical floating wind turbine under freak waves. Ocean Engineering, 269, 113464.
Stark C, Xu Y, Zhang M, et al. Study on applicability of energy-saving devices to hydrogen fuel cell-powered ships[J]. Journal of Marine Science and Engineering, 2022, 10(3): 388.
Zhang M. , et al. Real-time Control of Wave Energy Converter Based on LSTM RNN based Wave Prediction. Online conference, 28-29 April 2022.
Li T., Zhang M., et.al. Real-time Control of WECs Based on NAR,NARX and LSTM Artificial Neural Network. ISOPE2022, Shanghai.
Zhang M., et al. A Novel Conceptual Design of Modularised Offshore Green Hydrogen System, 42nd OMAE conference, Melbourne, Australia, 11-16 June 2022.
Yu S., Zhang M., et al. Pitch Motion Control of Spar-Type Floating Wind Turbines, 42nd OMAE conference, Melbourne, Australia, 11-16 June 2022.
Zhang D., Zhang M., et al. Hydrodynamic Modelling of Modularized Floating Photovoltaics Arrays, Melbourne, Australia, 42nd OMAE conference, 11-16 June 2022.
Zhang M., et al. Real-time Control of Wave Energy Converter Based on LSTM RNN based Wave Prediction. ICDM 2022 conference, Seoul, Republic of Korea, 28-29 April 2022.
Zhang M. Yuan Z.M. *. Time-optimal Autonomous Berthing Based on Nonlinear Model Predictive Control. 6th MASHCON 2022, Glasgow, 22-26 May 2022.
Zhang M., et al. Development of a Novel Wave-Force Prediction Model Based on Deep Machine Learning Algorithms. ISOPE2020, Virtual, October 2020.
Zhang M.. Development of a Novel Wave-force Prediction Model based on LSTM-NARX Algorithms. WSOS2020 workshop, Glasgow, 5-8 February 2020, Glasgow, UK.
Zhang M.. Real-time Control of Wave Energy Converter Based on LSTM Prediction based on LSTM-NARX Algorithms. WETNAOE2019 workshop, 14-15 November 2019, Hiroshima, Japan.

Project Involvement:

Apr 2022 - Present: Maritime Hydrogen Highway, Maritime Research and Innovation UK (MarRI-UK) initiative supported by the Department for Transport (DfT)
Sep 2021 - Apr 2022:Transition to hydrogen powered ocean-going and short-sea shipping with enabling retrofit technologies (TransShip), UK research innovate (UKRI).
Sep 2021 - Present: Investigation on Real-time Control Method of Wave Energy Converter Based on Machine Learning Wave Prediction, supported by National Natural Science Foundation of China (NSFC).
Sept 2018 - Jul 2021: Multibody system hydrodynamics | Zhang, Ming (PI), EPSRC (Engineering and Physical Sciences Research Council).
May 2023- Sept 2024: Disruptive Technologies for Enhancing UK Shipbuilding’s Productivity and Competitiveness (UK National Shipbuilding Office & MarRI-UK)
Maritime Robotics Society Academic Adviors of Autonomous Control Team