• United Kingdom

Accepting PhD Students

PhD projects

EY1: Biologically-Inspired Multi-Objective Design Optimisation for Space Mechatronic Systems

In future space missions, autonomous, intelligent and massively distributed mechatronic systems will play important roles. The space application domain presents unique challenges to the design of mechatronic systems. For example, due to the extremely limited and expensive resources available onboard, design optimisations are particularly needed for both power savings and performance improvement in satellite-based sensing and imaging. Thus, the development of efficient multi-objective design optimisation algorithms capable of optimising the space-based mechatronic systems is essential under the stringent requirements for power consumption, cost, mass, reliability, and performance improvement, etc.
The aim of this research is to develop novel and efficient bio-inspired optimisation approaches for multi-objective design-space exploration of space mechatronic systems. Its main research objectives are summarised as below:
1. Develop new bio-inspired algorithms for design exploration of space mechatronic systems under multiple design and environmental constraints.
2. Investigate algorithm performance, convergence, and design efficiency trade-off.
3. Investigate the computing requirement of bio-inspired algorithms for real-time response to application requirements under different environmental constraints.
4. Investigate the designs produced by the developed bio-inspired algorithms in terms of multiple objectives, such as cost, mass, reliability, and performance, etc.

EY 2: Brain-inspired Intelligent Control of Multiple Autonomous Systems for Space Applications.
In space application, multiple autonomous systems (MASs) can be more effective than a single autonomous system, for example, in information gathering and exploration tasks with multiple planetary robots. The potential for MASs cooperating together to accomplish challenging tasks has drawn together researchers from several fields, including robotics, control systems, and computer science. Biologically-inspired and intelligent control systems for MASs, including for Mars’ rovers and DARPA Challenges, have received a lot of research attention. For example, a fault-tolerant, Biologically Inspired System for Map-based Autonomous Rover Control has been developed in NASA’s Jet Propulsion Laboratory for long duration missions with multiple autonomous vehicles.
The general scientific objectives of this research are to address two fundamental research challenges related to the development of novel intelligent coordinated control of multi-agent systems, particularly in the context of MASs for space applications. The first research challenge is related to real-time information processing and utilisation, i.e., how to quickly and efficiently extract and analyse information acquired by the MASs. The second research challenge is concerned with designing adaptive autonomous controllers by exploiting the extracted and analysed information to cooperatively control the MASs, and also improve the MAS’s capabilities, such as surveillance, target acquisition and tracking, etc.
To realise these general scientific objectives, novel brain-inspired approaches are particularly appealing for extracting information, processing the extracted information into the design, online tuning, and adaptive switching of autonomous multi-agent controllers under complex and dynamic environments.

EY 3: Towards an Integrated Cognitive Control System for Autonomous Vehicles
The field of autonomous vehicle is a rapidly growing one which promises improved performance, fuel economy, emission levels, comfort and safety. The UK government is determined to address the challenges of tackling climate change, maintaining energy security, and solving transportation in a way that minimises costs and maximises benefits to the economy. Among all sources of CO2 emissions in the UK, the energy supply accounts for about 40%, followed by the transport for over 25%, and emissions from cars and vans account for 70% in domestic transport sector. Intelligent and efficient control is one of key issues in developing fully autonomous vehicles.
Given the similarity between the problem' domains of autonomous vehicle’s control and action selection in animals, this research aims to leverage new results from psychology and neurobiology and apply them to the control of autonomous vehicles. Towards this end, an integrated cognitive control system for autonomous vehicles is targeted in this research. We aim to harness general strategies for control based on high level analysis of human behavioural control.
The primary objective of this research is to uplift research collaborations from the current separate, point-to-point collaborations to a broader and deeper context with a more systematic, more coherent, and more coordinated synergised approach for developing an integrated cognitive control system for autonomous vehicles towards more reliable, more flexible and efficient, and more environmental friendly control solutions.

EY 4:Novel Intelligent and Optimal Decision-Making Paradigm for Autonomous Manufacturing
Today’s manufacturing has become more competitive as manufacturers need innovative and extremely agile processes along with increasing manufacturing automation and informatics complexity. The main aim of this research is to develop novel intelligent and optimal decision-making paradigm for autonomous manufacturing in an Industry 4 environment.
The focus of this research will be on the development of innovative smart decision-making strategies to coordinate multiple agents and make collaborative and optimal decision and take group actions by concurrently dealing with multiple objectives under extreme environmental constrains arising from both internal (such as manufacturing process disturbances, e.g., one industrial robot breaks down) and external (e.g., partial and inconsistent information). In the smart factory, all the manufacturing resources are modelled as intelligent agents/entities. Each agent has the ability to percept, reason, make decision, and take actions without (or with limited) human interferences.
The key research challenge lies in the intelligent and optimal decision-making mechanism for the agents in the smart manufacturing system to independently make decisions and plan their own tasks based on their own reasons about their environment, state/situation and the likely actions taken by other agents.

EY 5: Advanced Artificial Intelligence in Automatic Human-Machine Knowledge Transfer
This research is concerned with the way that how to automatically transfer human expert/operator’s knowledge obtained in existing processes and experiences into intelligent agents (e.g., industrial robots) to advance the capabilities of intelligent agents in an autonomous manufacturing system. Toward this end, an advanced intelligent system consisting of intelligent knowledge-based expert system and artificial neural network (ANN) models will be explored in this research. The use of ANN models will make the system intelligent by learning patterns from existing manufacturing data and process knowledge and use them for predicting the behaviour of manufacturing, which would result in reducing the lead time and cost considerably.

19972021

Research output per year

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Article
2020

Deep convolution network based emotion analysis towards mental health care

Fei, Z., Yang, E., Li, D. D. U., Butler, S., Ijomah, W., Li, X. & Zhou, H., 7 May 2020, In : Neurocomputing. 388, p. 212-227 16 p.

Research output: Contribution to journalArticle

1 Citation (Scopus)
Open Access
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1 Citation (Scopus)
7 Downloads (Pure)
Open Access
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General decay lag anti-synchronization of multi-weighted delayed coupled neural networks with reaction–diffusion terms

Huang, Y., Hou, J. & Yang, E., 29 Feb 2020, In : Information Sciences. 511, p. 36-57 22 p.

Research output: Contribution to journalArticle

2 Citations (Scopus)

Passivity and synchronization of coupled different dimensional delayed reaction-diffusion neural networks with dirichlet boundary conditions

Lin, S., Huang, Y. & Yang, E., 8 Jan 2020, In : Complexity. 2020, 21 p., 4987962.

Research output: Contribution to journalArticle

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Passivity and synchronization of coupled reaction-diffusion complex-valued memristive neural networks

Huang, Y., Hou, J. & Yang, E., 15 Aug 2020, In : Applied Mathematics and Computation. 379, 22 p., 125271.

Research output: Contribution to journalArticle

1 Citation (Scopus)

Recursive search-based identification algorithms for the exponential autoregressive time series model with coloured noise

Xu, H., Ding, F. & Yang, E., 29 Jan 2020, In : IET Control Theory and Applications . 14, 2, p. 262-270 9 p.

Research output: Contribution to journalArticle

Open Access
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1 Downloads (Pure)

Two-stage recursive identification algorithms for a class of nonlinear time series models with colored noise

Xu, H., Ding, F., Gan, M. & Yang, E., 10 Aug 2020, (Accepted/In press) In : International Journal of Robust and Nonlinear Control . p. 1-17 17 p.

Research output: Contribution to journalArticle

2019

A benchmark image dataset for industrial tools

Luo, C., Yu, L., Yang, E., Zhou, H. & Ren, P., 1 Jul 2019, In : Pattern Recognition Letters. 125, p. 341-348 8 p.

Research output: Contribution to journalArticle

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2 Citations (Scopus)
5 Downloads (Pure)

A novel semi-supervised convolutional neural network method for synthetic aperture radar image recognition

Yue, Z., Gao, F., Xiong, Q., Wang, J., Huang, T., Yang, E. & Zhou, H., 19 Mar 2019, In : Cognitive Computation. p. 1-12 12 p.

Research output: Contribution to journalArticle

Open Access
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12 Citations (Scopus)

A novel semi-supervised learning method based on fast search and density peaks

Gao, F., Huang, T., Sun, J., Hussain, A., Yang, E. & Zhou, H., 3 Feb 2019, In : Complexity. 2019, p. 1-23 23 p., 6876173.

Research output: Contribution to journalArticle

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2 Citations (Scopus)
6 Downloads (Pure)

A novel separability objective function in CNN for feature extraction of SAR images

Gao, F., Wang, M., Wang, J., Yang, E. & Zhou, H., 1 Mar 2019, In : Chinese Journal of Electronics. 28, 2, p. 423-429 7 p.

Research output: Contribution to journalArticle

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A novel visual attention method for target detection from SAR images

Gao, F., Liu, A., Liu, K., Yang, E. & Hussain, A., 31 Aug 2019, In : Chinese Journal of Aeronautics. 32, 8, p. 1946-1958 13 p.

Research output: Contribution to journalArticle

Open Access
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2 Citations (Scopus)
1 Downloads (Pure)

A survey on computer vision techniques for detecting facial features towards the early diagnosis of mild cognitive impairment in the elderly

Fei, Z., Yang, E., Li, D. D-U., Butler, S., Ijomah, W. & Zhou, H., 31 Jul 2019, In : Systems Science and Control Engineering. 7, 1, p. 252–263 12 p.

Research output: Contribution to journalArticle

Open Access
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4 Downloads (Pure)

Development of active soft robotic manipulators for stable grasping under slippery conditions

Luo, C., Wang, K., Li, G., Yin, S., Yu, L. & Yang, E., 8 Jul 2019, In : IEEE Access. 7, p. 97604-97613 10 p.

Research output: Contribution to journalArticle

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1 Downloads (Pure)

Enhanced feature extraction for ship detection from multi-resolution and multi-scene synthetic aperture radar (SAR) images

Gao, F., Shi, W., Wang, J., Yang, E. & Zhou, H., 18 Nov 2019, In : Remote Sensing. 11, 22, 22 p., 2694.

Research output: Contribution to journalArticle

Open Access
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2 Citations (Scopus)
2 Downloads (Pure)

Finite-time anti-synchronization of multi-weighted coupled neural networks with and without coupling delays

Hou, J., Huang, Y. & Yang, E., 1 Dec 2019, In : Neural Processing Letters. 50, 3, p. 2871-2898 28 p.

Research output: Contribution to journalArticle

Open Access
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1 Citation (Scopus)
Open Access
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3 Citations (Scopus)
2 Downloads (Pure)

Highly computationally efficient state filter based on the delta operator

Zhang, X., Ding, F., Xu, L. & Yang, E., 30 Jun 2019, In : International Journal of Adaptive Control and Signal Processing. 33, 6, p. 875-889 15 p.

Research output: Contribution to journalArticle

Open Access
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34 Citations (Scopus)
1 Downloads (Pure)

Modeling a nonlinear process using the exponential autoregressive time series model

Xu, H., Ding, F. & Yang, E., 28 Feb 2019, In : Nonlinear Dynamics. 95, 3, p. 2079-2092 14 p.

Research output: Contribution to journalArticle

Open Access
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23 Citations (Scopus)
Open Access
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17 Citations (Scopus)
Open Access
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2 Citations (Scopus)
14 Downloads (Pure)

Stability analysis of the high-order extended state observers for a class of nonlinear control systems

Gao, K., Song, J. & Yang, E., 1 Nov 2019, In : Transactions of the Institute of Measurement and Control. 41, 15, p. 4370-4379 20 p.

Research output: Contribution to journalArticle

Open Access
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1 Citation (Scopus)
2 Downloads (Pure)
Open Access
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67 Citations (Scopus)
2 Downloads (Pure)

The high-speed rotorcraft unmanned aerial vehicle path planning based on the biogeography-based optimization algorithm

Song, J., Zhao, M., Yang, E. & Lin, J., 6 May 2019, In : Advances in Mechanical Engineering. 11, 5, 12 p.

Research output: Contribution to journalArticle

Open Access
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1 Citation (Scopus)

UAV first view landmark localization with active reinforcement learning

Wang, X., Li, C., Yu, L., Han, L., Deng, X., Yang, E. & Ren, P., 1 Jul 2019, In : Pattern Recognition Letters. 125, p. 549-555 7 p.

Research output: Contribution to journalArticle

Open Access
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2 Citations (Scopus)
11 Downloads (Pure)

ψ-type stability of reaction–diffusion neural networks with time-varying discrete delays and bounded distributed delays

Hou, J., Huang, Y. & Yang, E., 7 May 2019, In : Neurocomputing. 340, p. 281-293 13 p.

Research output: Contribution to journalArticle

Open Access
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2 Citations (Scopus)
2018

A deep convolutional generative adversarial networks (DCGANs)-based semi-supervised method for object recognition in synthetic aperture radar (SAR) images

Gao, F., Yang, Y., Wang, J., Sun, J., Yang, E. & Zhou, H., 29 May 2018, In : Remote Sensing. 10, 6, 21 p., 846.

Research output: Contribution to journalArticle

Open Access
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22 Citations (Scopus)
10 Downloads (Pure)

A new algorithm of SAR image target recognition based on improved deep convolutional neural network

Gao, F., Huang, T., Sun, J., Wang, J., Hussain, A. & Yang, E., 26 Jun 2018, In : Cognitive Computation. 16 p.

Research output: Contribution to journalArticle

Open Access
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16 Citations (Scopus)
100 Downloads (Pure)

Autonomous robots for harsh environments: a holistic overview of current solutions and ongoing challenges

Wong, C., Yang, E., Yan, X-T. & Gu, D., 30 Jun 2018, In : Systems Science and Control Engineering. 6, 1, p. 213-219 7 p.

Research output: Contribution to journalArticle

Open Access
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8 Citations (Scopus)
92 Downloads (Pure)

Bubble density gradient with laser detection: a wake-homing scheme for supercavitating vehicles

Song, J., Bian, L., Yang, E. & Su, D., 18 Jun 2018, In : Advances in Mechanical Engineering. 10, 6, p. 1-12 12 p.

Research output: Contribution to journalArticle

Open Access
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1 Citation (Scopus)
14 Downloads (Pure)

Deep learning for vision-based micro aerial vehicle autonomous landing

Yu, L., Luo, C., Yu, X., Jiang, X., Yang, E., Luo, C. & Ren, P., 30 Jun 2018, In : International Journal of Micro Air Vehicles. 10, 2, p. 171-185 15 p.

Research output: Contribution to journalArticle

Open Access
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7 Citations (Scopus)
37 Downloads (Pure)

Energy minimization with one dot fuzzy initialization for marine oil spill segmentation

Ren, P., Xu, M., Yu, Y., Chen, F., Jiang, X. & Yang, E., 2 Jul 2018, In : IEEE Journal of Oceanic Engineering. 14 p.

Research output: Contribution to journalArticle

Open Access
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4 Citations (Scopus)
17 Downloads (Pure)

Gradient-based iterative parameter estimation for bilinear-in-parameter systems using the model decomposition technique

Chen, M., Ding, F. & Yang, E., 27 Nov 2018, In : IET Control Theory and Applications . 12, 17, p. 2380-2389 10 p.

Research output: Contribution to journalArticle

Open Access
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5 Citations (Scopus)
4 Downloads (Pure)

Parameter estimation algorithm for multivariable controlled autoregressive autoregressive moving average systems

Liu, Q., Ding, F. & Yang, E., 31 Dec 2018, In : Digital Signal Processing: A Review Journal. 83, p. 323-331 9 p.

Research output: Contribution to journalArticle

Open Access
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6 Citations (Scopus)

Semi-supervised generative adversarial nets with multiple generators for SAR image recognition

Gao, F., Ma, F., Wang, J., Sun, J., Yang, E. & Zhou, H., 17 Aug 2018, In : Sensors (Switzerland). 18, 8, 19 p., 2706.

Research output: Contribution to journalArticle

Open Access
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6 Citations (Scopus)
7 Downloads (Pure)

State filtering-based least squares parameter estimation for bilinear systems using the hierarchical identification principle

Zhang, X., Ding, F., Xu, L. & Yang, E., 4 Apr 2018, In : IET Control Theory and Applications . p. 1-10 10 p.

Research output: Contribution to journalArticle

Open Access
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76 Citations (Scopus)
13 Downloads (Pure)
2017
Open Access
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16 Citations (Scopus)
6 Downloads (Pure)

A novel active semisupervised convolutional neural network algorithm for SAR image recognition

Gao, F., Yue, Z., Wang, J., Sun, J., Yang, E. & Zhou, H., 1 Oct 2017, In : Computational Intelligence and Neuroscience. 2017, p. 1-8 8 p., 3105053.

Research output: Contribution to journalArticle

Open Access
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11 Citations (Scopus)
35 Downloads (Pure)

A novel target detection method for SAR images based on shadow proposal and saliency analysis

Gao, F., You, J., Wang, J., Sun, J., Yang, E. & Zhou, H., 6 Dec 2017, In : Neurocomputing. 267, p. 220-231 12 p.

Research output: Contribution to journalArticle

Open Access
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14 Citations (Scopus)
12 Downloads (Pure)

Combined state and parameter estimation for Hammerstein systems with time-delay using the Kalman filtering

Ma, J., Ding, F., Xiong, W. & Yang, E., 31 Aug 2017, In : International Journal of Adaptive Control and Signal Processing. 31, 8, p. 1139-1151 13 p.

Research output: Contribution to journalArticle

Open Access
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13 Citations (Scopus)
97 Downloads (Pure)

Design of high-isolation wideband dual-polarized compact MIMO antennas with multi-objective optimization

Lu, D., Wang, L., Yang, E. & Wang, G., 18 Dec 2017, In : IEEE Transactions on Antennas and Propagation. p. 1-6 6 p.

Research output: Contribution to journalArticle

Open Access
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10 Citations (Scopus)
55 Downloads (Pure)

Design of UHF fractal antenna for localized near-field RFID application

Tao, Y., Yang, E., Dong, Y. & Wang, G., 1 Jun 2017, In : Microwave and Optical Technology Letters. 59, 6, p. 1390-1394 5 p.

Research output: Contribution to journalArticle

Open Access
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26 Downloads (Pure)

Dual-branch deep convolution neural network for polarimetric SAR image classification

Gao, F., Huang, T., Wang, J., Sun, J., Hussain, A. & Yang, E., 31 May 2017, In : Applied Sciences. 7, 5, 18 p., 447.

Research output: Contribution to journalArticle

Open Access
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35 Citations (Scopus)
58 Downloads (Pure)

Left-handed metamaterial lens applicator with built-in cooling feature for superficial tumor hyperthermia

Tao, Y., Yang, E. & Wang, G., 1 Nov 2017, In : Applied Computational Electromagnetics Society Journal. 32, 11, p. 1029-1034 6 p.

Research output: Contribution to journalArticle

Open Access
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1 Citation (Scopus)
9 Downloads (Pure)

Molecular dynamics simulation of persistent slip bands formation in nickel-base superalloys

Huang, J-F., Wang, Z-L., Yang, E-F., McGlinchey, D., Luo, Y-X., Li, Y. & Chen, Y., 28 Feb 2017, In : International Journal of Automation and Computing. 14, 1, p. 68-79 12 p.

Research output: Contribution to journalArticle

Open Access
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36 Downloads (Pure)

Visual saliency modeling for river detection in high-resolution SAR imagery

Gao, F., Ma, F., Wang, J., Sun, J., Yang, E. & Zhou, H., 24 Nov 2017, In : IEEE Access. 6, p. 1000-1014 15 p.

Research output: Contribution to journalArticle

Open Access
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36 Citations (Scopus)
32 Downloads (Pure)
2016

A novel semisupervised support vector machine classifier based on active learning and context information

Gao, F., Lv, W., Zhang, Y., Sun, J., Wang, J. & Yang, E., 2 Apr 2016, In : Multidimensional Systems and Signal Processing. 20 p.

Research output: Contribution to journalArticle

Open Access
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5 Citations (Scopus)
50 Downloads (Pure)