Professor Jiamei Deng, Professor

Professor Jiamei Deng

Professor

Dr. Jiamei Deng joined Leeds Beckett University as a Professor in Artificial Intelligence, Control, and Energy in 2015. Her research has been focused on data analytics, artificial intelligence, and control system design for different applications, such as biomedical engineering, civil engineering, automotive engineering, nuclear power plants, other energy systems.  She is holding two EU patents. Jiamei is also the sole author of one monograph, the main author of three book chapters, and has authored /co-authored over one hundred papers including prestigious journals, such as IEEE Transactions on Neural Networks and Learning Systems,  IEEE Transaction on Industrial Electronics, Engineering Applications of Artificial Intelligence.

Jiamei’s recent government funded projects:

  1. Leading Principal Investigator (PI) for three linked projects (EP/M018717/1, EP/M018709/1, EP/M018415/1), Smart on-line monitoring for nuclear power plants (SMART) , EPSRC, 2015-2018. This project used data science and artificial intelligence to generate monitoring tools for nuclear power plants.
  2. PI: Fault tolerant control for increased safety and security of nuclear power plants , EPSRC, 2018-2022. This project has been using data science, artificial intelligence, and control theory to design an integrated module for increased safety and security of nuclear power plants.
  3. Co-I: Smart Meter Research Portal, EPSRC, 2017-2022.
  4. The Information about the above three projects can be found here: https://gtr.ukri.org/person/61E85F70-6E06-40DF-9345-EB87626602E8

  5. PI: Research on Fault tolerant control, Royal Academy of Engineering, 2018.

Professional memberships

  1. Member of EPSRC Peer Review College
  2. Member of Smart Energy Research Lab - https://serl.ac.uk/about-who-we-are/
  3. Senior Member of IEEE
  4. Fellow of Higher Education Academy

Current Teaching

  1. PhD supervision
  2. Master level individual project supervision

Teaching Master level modules:

  • Data analytics and visualization
  • Research practice
  • Engineering systems control

Research Interests

Big data, artificial intelligence, control system design, energy system efficiency and safety 

Professor Deng welcomes any enquiry about these topics either from industry or research organization. She also welcomes motivated and qualified applicants who are interested in PhD study in her group.

Professor Jiamei Deng, Professor

Selected Outputs

  • Deng J; Stobart R; liu C; Winward E (In press) Explicit Model Predictive Control of the Diesel Engine Fuel Path.

  • Deng J; Surjagade P; Deng J; Vajpayee V; Becerra, V; Shimjith SR; Arul AJ (2022) Fractional Order Integral Sliding Mode Control for PWR Nuclear Power Plant.

  • Naimi A; Jiamei D; Shimjith SR; Arul AJ; Deng J (2022) Intelligent Feedback Linearisation-based Control for a Pressurised Water Reactor System.

  • Vajpayee V; Becerra V; Bausch N; Deng J (2022) Wavelet-based Model Predictive Control of PWR Nuclear Reactor using Multi-Scale Subspace Identification.

  • Banerjee S; Deng J; Gorse C; Vajpayee V; Becerra VM; Bausch N; Shimjith SR; Arul J (2020) ANN Based Sensor and Actuator Fault Detection in Nuclear Reactors.

  • Naimi A; Deng J; Abdulrahman A; Vajpayee V; Victor B; Bausch N (2020) Dynamic Neural Network-based System Identification of a Pressurized Water Reactor.

  • Vajpayee V; Becerra V; Bausch N; Banerjee S; Deng J; Shimjith SR; Arul AJ (2020) Disturbance Observer-based Subspace Predictive Control of a Pressurized Water-type Nuclear Reactor.

  • Vajpayee V; Becerra V; Bausch N; Banerjee S; Deng J; Shimjith SR; Arul AJ (2020) Robust Subspace Predictive Control based on Integral Sliding Mode for a Pressurized Water Reactor.

  • Vajpayee V; Becerra V; Bausch N; Banerjee S; Deng J; Shimjith SR; Arul AJ (2020) Gain Scheduled Subspace Predictive Control of a Pressurized Water-type Nuclear Reactor.

  • Deng J; Banerjee S (2020) LMI based robust PID controller design for PWR with bounded uncertainty using interval approach.

  • Tian D; Deng J; Vinod G; Santhosh TV (2019) A constraint-based random search algorithm for optimizing neural network architectures and ensemble construction in detecting loss of coolant accidents in nuclear power plants.

  • Tian D; Deng J; Zio E; Maio F; Liao F (2018) Failure modes detection of nuclear systems using machine learning.

  • Tian D; Deng J; Vinod G; Santhosh TV (2018) Selecting a minimum training set for neural networks using Short-Time fourier transform in detecting loss of coolant accidents in nuclear power plants.

  • Wang M; Deng J; Pattinson C; Richardson S (2017) A Fuzzy Controller for Fault Tolerant Control of Nuclear Reactor.

  • Khanjani K; Deng J; Ordys A (2014) Controlling variable coolant temperature in internal combustion engines and its effects on fuel consumption.

  • Levermore T; Ordys A; Deng J (2014) A review of driver modelling.

  • Chan KY; Ordys A; Duran O; Volkov K; Deng J (2014) Adaptive neuro-fuzzy method to estimate virtual SI engine fuel composition using residual gas parameters.

  • Deng J; Ordys A (2014) Modelling and control of hybrid systems - A forward look.

  • Zhao D; Liu C; Stobart R; Deng J; Winward E (2013) Explicit model predictive control on the air path of turbocharged diesel engines.

  • Chan KY; Ordys A; Duran O; Volkov K; Deng J (2013) SI engine simulation using residual gas and neural network modeling to virtually estimate the fuel composition.

  • Sedyono J; Hadavinia H; Deng J; Marchant DR; Garcia J (2012) Optimization of the stacking sequence of laminated composite plates under buckling loads.

  • Deng J; Ordys A; Yawei Wang (2012) Input choices of Particulate Matter Models for Diesel Engines.

  • Vajpayee V; Becerra V; Bausch N; Deng J; Shimjith SR; Arul AJ (2021) L₁-Adaptive Robust Control Design for a Pressurized Water-Type Nuclear Power Plant. IEEE Transactions on Nuclear Science, 68 (7), pp. 1381-1398.

    https://doi.org/10.1109/TNS.2021.3090526

  • Vineet V; Becerra V; Bausch N; Deng J; Shimjith SR; Arul J (2021) LQGI/LTR based Robust Control Technique for a Pressurized Water Nuclear Power Plant. Annals of Nuclear Energy, 154

    https://doi.org/10.1016/j.anucene.2020.108105

  • Sun M; Liao F; Deng J (2021) Design of an optimal preview controller for linear discrete-time periodic systems. Transactions of the Institute of Measurement and Control, 43 (12), pp. 2637-2646.

    https://doi.org/10.1177/01423312211002585

  • Xie H; Liao F; Chen Y; Zhang X; Li M; Deng J (2021) Finite-time Bounded Tracking Control for Fractional-order Systems. IEEE Access

    https://doi.org/10.1109/ACCESS.2021.3049919

  • Vajpayee V; Becerra V; Bausch N; Deng J; Shimjith SR; Arul AJ (2021) Robust-optimal integrated control design technique for a pressurized water-type nuclear power plant. Progress in Nuclear Energy, 131 pp. 103575-103575.

    https://doi.org/10.1016/j.pnucene.2020.103575

  • Vajpayee V; Becerra V; Bausch N; Deng J; Shimjith SR; Arul AJ (2020) Dynamic modelling, simulation, and control design of a pressurized water-type nuclear power plant. Nuclear Engineering and Design, 370 pp. 110901-110901.

    https://doi.org/10.1016/j.nucengdes.2020.110901

  • Liao F; Cui L; Lu Y; Deng J (2020) Preview Tracking Control of Linear Periodic Switched Systems with Dwell Time. Mathematical Problems in Engineering, 2020 pp. 1-9.

    https://doi.org/10.1155/2020/8395683

  • Becerra VM; Vajpayee V; Bausch N; Santhosh TV; Vinod G; Deng J (2020) Estimation of Radioactivity Release Activity Using Non-Linear Kalman Filter-Based Estimation Techniques. Energies, 13 (15), pp. 3985-3985.

    https://doi.org/10.3390/en13153985

  • Xie H; Liao F; Usman; Deng J (2020) Design of preview controller for a type of discrete-time interconnected systems. Measurement and Control, pp. 002029401989874-002029401989874.

    https://doi.org/10.1177/0020294019898745

  • Jia C; Liao F; Deng J (2019) Impulse Elimination and Fault-Tolerant Preview Controller Design for a Class of Descriptor Systems. Mathematical Problems in Engineering, 2019 pp. 1-13.

    https://doi.org/10.1155/2019/3857275

  • Xie H; Liao F; Deng J (2019) Preview Tracking Control for Continuous-Time Singular Interconnected Systems. Mathematical Problems in Engineering, 2019

    https://doi.org/10.1155/2019/6175837

  • Deng J; Liao F; Yu X (2019) Tracking controller design with preview action for a class of Lipschitz nonlinear systems and its applications. Circuits, Systems, and Signal Processing

    https://doi.org/10.1007/s00034-019-01313-9

  • Liao F; Jia C; Malik U; Yu X; Deng J (2019) The preview control of a class of linear systems and its application in the fault-tolerant control theory. International Journal of Systems Science

    https://doi.org/10.1080/00207721.2019.1587028

  • Tian D; Deng J; Vinod G; Santhosh TV; Tawfik H (2018) A constraint-based genetic algorithm for optimizing neural network architectures for detection of loss of coolant accidents of nuclear power plants. Neurocomputing, 322 pp. 102-119.

    https://doi.org/10.1016/j.neucom.2018.09.014

  • Yu X; Liao F; Deng J (2018) Robust Preview Control for a Class of Uncertain Discrete-Time Lipschitz Nonlinear Systems. Mathematical Problems in Engineering, 2018

    https://doi.org/10.1155/2018/4606389

  • Lu Y; Liao F; Deng J; Pattinson C (2018) Cooperative optimal preview tracking for linear descriptor multi-agent systems. Journal of the Franklin Institute, 356 (2), pp. 908-934.

    https://doi.org/10.1016/j.jfranklin.2018.01.016

  • Yu X; Liao F; Deng J (2018) Preview Tracking Control for a Class of Differentiable Nonlinear Systems. Arabian Journal for Science and Engineering, 43 (6), pp. 3259-3268.

    https://doi.org/10.1007/s13369-017-3040-y

  • Liao F; Wu Y; Yu X; Deng J (2018) Finite-Time Bounded Tracking Control for Linear Discrete-Time Systems. Mathematical Problems in Engineering, 2018

    https://doi.org/10.1155/2018/7017135

  • Liao F; Wang Y; Lu Y; Deng J (2017) Optimal preview control for a class of linear continuous-time large-scale systems. Transactions of the Institute of Measurement and Control, 40 (14), pp. 4004-4013.

    https://doi.org/10.1177/0142331217740946

  • Lu Y; Liao F; Deng J; Liu H (2017) Cooperative global optimal preview tracking control of linear multi-agent systems: an internal model approach. International Journal of Systems Science, 48 (12), pp. 2451-2462.

    https://doi.org/10.1080/00207721.2017.1318971

  • Liao F; Yu X; Deng J (2017) Absolute stability of time-varying delay Lurie indirect control systems with unbounded coefficients. Advances in Difference Equations, 38

    https://doi.org/10.1186/s13662-017-1094-5

  • Li L; Liao F; Deng J (2017) H∞ Preview Control of a Class of Uncertain Discrete-Time Systems. Asian Journal of Control

    https://doi.org/10.1002/asjc.1466

  • Wu J; Liao F; Deng J (2016) Optimal Preview Control for a Class of Linear Continuous Stochastic Control Systems in the Infinite Horizon. Mathematical Problems in Engineering, 2016

    https://doi.org/10.1155/2016/7679165

  • Liao F; Liao Y; Deng J (2016) The Application of Predictor Feedback in Designing a Preview Controller for Discrete-Time Systems with Input Delay. Mathematical Problems in Engineering, 2016

    https://doi.org/10.1155/2016/3023915

  • Chan KY; Ordys A; Duran O; Volvov K; Deng J (2014) Minimizing engine emissions using state-feedback control with LQR and artificial intelligence fuel estimator. International Journal of Innovative Research in Science, Engineering and Technology, 2 (3), pp. 1-9.

    http://ijirts.org/volume2issue3/IJIRTSV2I3052.pdf

  • Zhao D; Liu C; Stobart R; Deng J; Winward E; Dong G (2013) An explicit model predictive control framework for turbocharged diesel engines. IEEE Transactions on Industrial Electronics, 61 (7), pp. 3540-3552.

    https://doi.org/10.1109/TIE.2013.2279353

  • Deng J (2013) Dynamic neural networks with hybrid structures for nonlinear system identification. Engineering Applications of Artificial Intelligence, 26 (1), pp. 281-292.

    https://doi.org/10.1016/j.engappai.2012.05.003

  • Jiamei Deng; Maass B; Stobart R (2012) Minimum Data Requirement for Neural Networks Based on Power Spectral Density Analysis. IEEE Transactions on Neural Networks and Learning Systems, 23 (4), pp. 587-595.

    https://doi.org/10.1109/tnnls.2012.2183887

  • Deng J; Maass B; Stobart R; Winward E; Yang Z (2011) Accurate and continuous fuel flow rate measurement prediction for real time application. SAE International Journal of Engines, 4 pp. 1724-1737.

    http://eprints.kingston.ac.uk/24246/

  • Winward E; Deng J; Stobart R (2010) Innovations in experimental techniques for the development of fuel path control in diesel engines. SAE International Journal of Fuels and Lubricants, 3 pp. 594-613.

    http://eprints.kingston.ac.uk/24247/

  • Deng J; Becerra VM; Stobart R (2009) Input constraint handling in a MPC/Feedback linearization scheme. International Journal of Applied Mathematics and Computer Science, 19 pp. 219-232.

    http://eprints.kingston.ac.uk/24245/

  • Santosh TV; Vinod G; Vijayan PK; Deng J (2018) PCA-Based Neural Network Model for Identification of Loss of Coolant Accidents in Nuclear Power Plants. In: Technology for Smart Futures. Springer International Publishing, pp. 345-354.

  • Tian D; Deng J; Vinod G; Santhosh TV; Tawfik H (2018) A Neural Networks Design Methodology for Detecting Loss of Coolant Accidents in Nuclear Power Plants. In: Applications of Big Data Analytics. Springer International Publishing, pp. 43-61.