Professor Derek A Linkens
Emeritus Professor

Professor D A LinkensAddress:
Professor Derek A Linkens FREng
Department of Automatic Control and Systems Engineering
University of Sheffield
S1 3JD
Tel: (+44) (0)114 222 5133
Fax: (+44) (0)114 222 5164
Room: C4b, Amy Johnson Building

Research interests
Research Grants (recent)
Key publications since 2001


Professor Derek Linkens joined the Department of Automatic Control and Systems Engineering in 1969 soon after its formation. He served as its Head of Department from 1988 to 1993, and was then Dean of Engineering from 1993 to 1996.

Prior to coming to Sheffield he worked in industry, initially with GEC Plessey, Ilford developing underwater weapons and then with GEC Elliot Flight Automation, Rochester in research into numerous aspects of flight guidance, autopilot design (Concorde) and avionics automatic testing.

He has been involved actively with the professional institutes of the IEE (now IET) and the Inst MC for which he was President in 1993, having fulfilled several other positions both prior to and after that time. He was awarded the Sir Harold Hartley silver medal in 1994 for `contributions to the technology of measurement and control of outstanding merit´. He was elected to a Fellowship of the Royal Academy of Engineering in 2005. He has been active in several Networks of Excellence in Europe and is currently the Technical Chair of NiSIS (Nature-inspired Smart Information Systems).

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Research interests

Professor Linkens has published over 400 refereed papers in academic journals and conference proceedings. Eight of these papers have received prize awards.

He has been active in biomedical systems engineering for over 30 years, initially in mathematical modelling of the human digestive tract. Subsequent areas of research were in cardio-respiratory modelling and identification, anaesthesia monitoring and control, and patient ventilator management. Other topics have been pharmaceutical drug modelling and optical materials processing. This has encompassed several areas of intelligent systems including expert systems, neuro-fuzzy modelling and self-organising fuzzy control. In recent years these techniques have been applied in the very different area of metal properties prediction and control. This has incorporated microstructural analysis and modelling within IMMPETUS (Institute for Microstructual and Mechanical Process Engineering: The University of Sheffield), of which he was a Co-founder and subsequent Director. This has led to innovative hybrid intelligent modelling architectures for a number of aluminium and steel alloys.

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Research Grants (recent)

EU FP6 Coordination Action (CA) `Nature-inspired Smart Information Systems´, 01/02/2005 to 31/01/2008, Euro140,000

EPSRC IMMPETUS Phase 2 (Senior Research Fellow),"Thermomechanical Processing: Metallurgy, Mechanics and Modelling",01/08/2002 to 31/07/2007, £3,850,000

EPSRC IMMPETUS Phase 1,´Advanced Models for Improved Planning and Control in Hot Working of Metals´, 01/08/1997 to 31/07/2002, £2,764,049

EPSRC `Predictive Modelling and Control of Patient Management in Intensive Care Unit´, 13/12/1999 to 12/03/2003, £167,815

EPSRC `From Processing to Properties: Characterisation of Toughness, 01/10/2000 to 30/09/2003, £285,760

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Key publications since 2001

Abbod, M. F., D. A. Linkens, Q. Zhu and M. Mahfouf (2002). `Semi-Physical Modelling of Internal States for Aluminium Alloys.´ Materials Science and Engineering A: Structural Materials: Properties Microstructure and Processing A333: 397-408.

Ting, C. H., A. Angel and D. A. Linkens (2002). `Neural network modelling of the effects of anaesthetic agents on the somatosensory pathways.´ Biol. Cybernetics 88:99-107.

Yang, Y.Y., D. A. Linkens and M. Mahfouf (2003). `Genetic Algorithms and Hybrid Neural Network Modelling for Aluminium Stress-Strain Prediction.´ I Mech E Proceedings: Part I - Journal of Systems and Control Engineering 217: 7-21.

Catto,J.W.F.,Linkens,D.A.,Abbod,M.F.,Chen,Minyou,Burton,J.L.,Feeley,K.M. and Hamdy, F.C. (2003). `Artificial Intelligence in predicting bladder cancer outcome: a comparison of neuro-fuzzy modelling and artificial neural networks.´ Clinical Cancer Research 9 (4172-4177).

Chen, M. and D. A. Linkens (2004). `Rule-base self-generation and simplification for data-driven fuzzy models.´ Fuzzy Sets and Systems 142(2): 243-265.

Kwok, H. F., D. A. Linkens, M. Mahfouf, G. H. Mills (2004). `SIVA: A hybrid knowledge-and-model-based advisory system for intensive care ventilators.´ IEEE Transactions on Information Technology in Biomedicine (TITB) 8(2): 161-172.

Abbod, M. F., C. M. Sellars, D. A. Linkens, Q. Zhu, M. Mahfouf (2005). `Validation and generalisation of hybrid models for flow stress and recrystallisation behaviour of aluminium alloys.´ Materials Science and Engineering, A: Structural Materials: Properties Microstructure and Processing 395: 35-46.

Catto, J.W.F., Abbod, M.F., Linkens, D.A. and Hamdy, F.C (2006) `Neuro-fuzzy modelling: an accurate and interpretable method for predicting bladder cancer progression.´ J Urology 175 (474-479).

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