Professor Mahdi Mahfouf

Head of the Intelligent Systems Research Laboratory

Professor Mahdi MahfoufAddress:
Professor Mahdi Mahfouf, Ing.Dipl. (Hons), MPhil, PhD, FIMA, CEng, CMath, FIET, FInstMC
Department of Automatic Control and Systems Engineering
The University of Sheffield
S1 3JD
Tel: (+44) (0)114 222 5607
Fax: (+44) (0)114 222 5624

Research interests

Fuzzy and neural fuzzy systems for modelling and control

The Principle of Incompatibility, as explained by L.A. Zadeh, stipulates that interpretability and precision are incompatible properties for some topologies. The research work we have hitherto undertaken within our Group at ACSE tries to push the capabilities of particularly fuzzy logic based algorithms further in order to ‘elicit’ architectures that are capable of achieving a high level of accuracy without significant compromises on transparency.

Another aspect of my Group’s research relates to incorporating Bayesian (probabilistic) reasoning within ‘certainty’ thinking epitomised in fuzzy logic theory to form a powerful formalism for solving complex modelling problems.

Research work on Fuzzy control currently focuses on eliciting self-organising control (SOC) architectures suitable for on-line applications.

Mahfouf, M; Abbod, MF; Linkens, DA Online elicitation of Mamdani-type fuzzy rules via TSK-based generalized predictive control, IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS Volume: 33 Issue: 3 Pages: 465-475 Published: JUN 2003

Modelling and Decision Support in Biomedicine

Monitoring Equipment used in ICU

We have been active in research in Biomedicine for more than 3 decades now when my mentor, Professor D.A. LINKENS, started exploring feedback control for muscle relaxation therapy in dogs and humans. When I joined his Research Group in 1985 as a research student we became the first researchers to apply successfully fuzzy logic to control the administration of muscle relaxant to humans. This was then followed by our own real-time adaptive version of SISO and MIMO Generalised Predictive Control (GPC) of muscle relaxation and Depth of Anaesthesia to humans in the operating theatre. Subsequent and current research activities close to this area include:

• Modelling and control of Depth of Anaesthesia (DOA)
• Fuzzy modelling and decision support in general and cardiac intensive care units (ICU and CICU)
• Signal processing and psycho-physical modelling and adaptive fuzzy control for Operational Functional State (OFS) in humans: Investigations into Man-Machine interactions

Generalized Predictive Control (GPC) in the Operating Theater., Mahfouf, M; Linkens, DA; Asbury, AJ; et al. IEEE Proceedings - D Control Theory and Applications Volume: 139 Issue: 4 Pages: 404-420 Published: JUL 1992

A hybrid hierarchical decision support system for cardiac surgical intensive care patients. Part I: Physiological modelling and decision support system design., Denai, Mouloud A; Mahfouf, Mahdi; Ross, Jonathan J, Artificial intelligence in medicine Volume: 45 Issue: 1 Pages: 35-52 Published: 2009-Jan (Epub 2008 Dec 27)

Cabin Air Management System (aCAMS)

A photo-shot of a volunteer engaged with the auto-enhanced Cabin Air Management System (aCAMS) while his vital signs are being monitored via a sensory-measurement system.

L.A.T Salomao, M. Mahfouf, E. El-Samahy and Ching-Hua Ting (2016) “Psycho-Physiologically-Based Real Time Adaptive General Type 2 Fuzzy Modelling and Self-Organising Control of Operator Performance Undertaking a Cognitive Task”, IEEE Transactions on Fuzzy Systems, Special Issue on Brain Computer Interface (BCI)”, 25(1):43-57.

Real-Time Adaptive Automation System Based on Identification of Operator Functional State in Simulated Process Control Operations, Ting, Ching-Hua; Mahfouf, Mahdi; Nassef, Ahmed; et al., IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS Volume: 40 Issue: 2 Pages: 251-262 Published: MAR 2010.

A Systems Engineering Approach to modelling and optimisation for metal processing: Investigations into 'right-first-time' production

A major aspect of this research relates to investigations into advanced multi-scale models of materials processing with predictive capabilities of the final micro-macro properties. Such models are embedded within the themes of Cellular Automata (2D and 3D), Finite Element (FE) and linguistic granules oriented neural fuzzy architectures. Further research activities concern model structure parameter optimisation and metal properties control via powerful constrained multi-objective optimisation techniques with economical and societal impacts.

Paradigm for the scheduling of a continuous walking beam reheat furnace using a modified genetic algorithm, Broughton, Jonathan S.; Mahfouf, Mahdi; Linkens, Derek A., MATERIALS AND MANUFACTURING PROCESSES Volume: 22 Issue: 5-6 Pages: 607-614 Published: 2007

Parameter optimisation of stress-strain constitutive equations using genetic algorithms, Yang, YY; Mahfouf, M; Linkens, DA, JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY Volume: 19 Supplement: 1 Pages: 5-8 Published: 2003

A population adaptive based immune algorithm for solving multi-objective optimization problems, Chen, Jun; Mahfouf, Mahdi, Edited by: Bersini, H; Carneiro, J Conference: 5th International Conference on Artificial Immune Systems Location: Oeiras, PORTUGAL Date: SEP 04-06, 2006, Sponsor(s): Univ Libre Bruxelles, RIDIA Lab; Inst Gulbenkian Cienc, ARTIFICIAL IMMUNE SYSTEMS, PROCEEDINGS Book Series: LECTURE NOTES IN COMPUTER SCIENCE Volume: 4163 Pages: 280-293 Published: 2006

3-D response surface

3-D response surface relating to a 3-rule fuzzy model showing the mapping between inputs and output for Friction-Stir Welding (FSW) of aluminium developed in collaboration with TWI Ltd. (UK).

Smart Tensegrity Structures: An Active Reconfigurable Structural Control Concept for Self-Healing Variable Geometry Applications

Tensegrity structures date back to the late 1940s when Buckminster Fuller used the term tensegrity as a contracted form of the two words tension and integrity to describe Kenneth Snelson’s structure. Tensegrity structures consist of two components: components in tension and those in compression, which shall be denoted as cables and bars, respectively. From a control engineering perspective, this class of structures are the ideal candidates for deployable structures] for they are capable of undergoing large displacements and can be of lightweight since these structures are obtained by optimal arrangement of material components. In addition to their lightweight and aesthetic value, tensegrity structures have other very interesting properties which motivate engineering research into these types of structures; these include mass efficiency, scalability, possibility of reliable model and accurate control, among others.

The research aim is to integrate for the first time systems and control engineering concepts within tensegrity structures which will include design, control, form-finding, Fault Detection Isolation and Accommodation (FDIA) as well as shape morphing as a truly through-process process.

Schematic Diagram Relating to Research into Tensegrity

Schematic Diagram relating to my research into tensegrity

Tensegrity Structure using 3 bars and 3 cables

A tensegrity structure using 3 bars and 3 cables


Professor Mahfouf is the holder of numerous EPSRC and EU grants currently totalling more than £2M.

Research Contracts

Professional Activities and Recognition

  • Member of the International Federation of Automatic Control (IFAC) Technical Committee on Mining, Mineral, and Metal Processing (MMM).
  • Member of the International Federation of Automatic Control (IFAC) Technical Committee on Biomedical Engineering.
  • Member of the EPSRC College System For 'General Engineering' (2003-).
  • Member of the Editorial Board of the International Journal of Simulation Systems Science and Technology.
  • External Examiner for UK and overseas PhD, MPhil Degrees; BSc (BEng), and MSc Courses.
  • Member of several Conference IPC's.
  • Advisor to UK and overseas Institutions on Senior Academic Appointments and Promotions.

Recent Key Publications

  1. O. Obajemu, M. Mahfouf and J.W.F. Catto (2017), “A New Fuzzy Modelling Framework for Integrated Risk Prognosis and Therapy of Bladder Cancer Patients”, IEEE Transactions on Fuzzy Systems, In Press.
  2. Wafa H. AlAlaween, B. Khorsheed, M. Mahfouf, I. Gabbott, G.K. Reynolds and A.D. Salman (2017), “Transparent Predictive Modelling of the Twin Screw Granulation Process using a Compensated Interval Type-2 Fuzzy System”, European Journal of Pharmaceutics and Biopharmaceutics, In Press.
  3. Wafa H. AlAlaween, M. Mahfouf and A.D. Salman (2017), “Integrating the Physics with Data Analytics for the Hybrid Modeling of the Granulation Process”, American Institute of Chemical Engineers- AIChE (Particle Technology and Fluidization), In Press.
  4. L.A.T Salomao, M. Mahfouf, E. El-Samahy and Ching-Hua Ting (2016) “Psycho-Physiologically-Based Real Time Adaptive General Type 2 Fuzzy Modelling and Self-Organising Control of Operator Performance Undertaking a Cognitive Task”, IEEE Transactions on Fuzzy Systems, Special Issue on Brain Computer Interface (BCI)”, 25(1):43-57.
  5. Wafa’ H. AlAlaween, M. Mahfouf and Agba D. Salman (2016), ‘Predictive Modelling of the Granulation Process Using a Systems-Engineering Approach’, Powder Technology- D, 302: 265–274.
  6. Guangrui Zhang, M. Mahfouf, Musa Abdulkareemc, Sid-Ahmed Gaffour, Yong-Yao Yang, Olusayo Obajemu, John Yates, Sabino Ayvar Soberanise, Christophe Pinna (2016) 'Hybrid-modelling of compact tension energy in high strength pipeline steel using a Gaussian Mixture Model based error compensation', Applied Soft Computing, 48, pp 1-12.
  7. Datta S, Mahfouf, M, Qiang Zhang, Imprecise knowledge based design and development of titanium alloys for prosthetic applications (2015), Journal of the Mechanical Behavior of Biomedical Materials, 53, 350-365.
  8. Chen, J, Mahfouf, M, and Sidahmed, G (2015). A new holistic systems approach to the design of heat treated alloy steels using a biologically inspired multi-objective optimisation algorithm. Engineering Applications of Artificial Intelligence (EAAI), 37, 103-114.
  9. Abdulkareem M, Mahfouf M, Theilliol D. (2015). Pole-Placement for Collocated Control of Flexible Structures, International Journal of Structural Stability and Dynamics, 16.
  10. Zhang Qiang, Mahfouf M, et al. (2015). Multi-objective Optimal Design of Friction Stir Welding Considering Quality and Cost Issues, Science and Technology of Welding and Joining, 20(7).
  11. Vertyagina,Y., and Mahfouf, M (2014). A 3D cellular automata model of the abnormal grain growth in austenite. Journal of Materials Science, 50(2), 745-754.