Jobrun Nandong

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Associate Prof. Dr. Jobrun Nandong
MEng (Imperial), PhD (Curtin), ACGI, AMIChemE
Associate Professor
Chemical Engineering

Contact Details
Telephone: +60 85 443939 extn: 2412 
Location: Skylark 3 Room 322
Email: jobrun.n@curtin.edu.my

PROFESSIONAL BACKGROUND

  • 2015 Associate Professor, Department of Chemical Engineering, Curtin University Sarawak, Malaysia
  • 2014 Chair of Intelligent System, Design and Control Research Area, Faculty of Engineering and Science, Curtin University Sarawak, Malaysia
  • 2009 Senior Lecturer, Department of Chemical Engineering, Curtin University Sarawak, Malaysia
  • 2006 – 2010 PhD (part-time), Curtin University; thesis “Modelling and Control Strategies of Extractive Fermentation: Partial Control Approach”
  • 2005 – 2008 Lecturer, Department of Chemical Engineering, Curtin University of Technology, Sarawak Campus, Malaysia
  • 2001 – 2004 A/Lecturer, Department of Chemical Engineering, Curtin University of Technology, Sarawak Campus, Malaysia
  • 2000 – 2001 Technical Project Officer, Industrial Estate Development Section, Ministry of Industrial Development, Sarawak
  • 1995 – 1999 MEng, Imperial College London, UK
  • 1993 – 1995 A-Level, Cambridge Tutor College, UK

RESEARCH INTERESTS

Multi-Scale Control Theory – A Nature-Inspired Way

Dr. Jobrun Nandong is a founding member (with Dr. Zhuquan Zang) of the recently reported Multi-Scale Control (MSC) Theory. Their theory represents a paradigm shift in control system design, in which the controller is constructed based on a sum of basic (multi-scale) plant modes. This control design approach is entirely different from those in conventional control designs where the controller is often constructed based on the lumped plant modes, i.e., entirely based on the slow dominant modes. In general, the MSC theory attempts to adopt some of the control patterns found in natural environments such as those in living organisms. Although the present MSC theory is only partially developed, they have successfully devised based on the theory several new control design techniques for multivariable, feedforward, cascade as well as PID control systems. Presently they are still developing a General MSC Theory, which in future will provide among others a new efficient method for developing super advanced intelligent control system based on a complex integration of multi-scale feedback control structures.

Research works in progress include:

  • Development of the General MSC Theory.
  • Construction of efficient procedures of decentralized and centralized PID control system designs.
  • Optimal design, modelling and control of hydrogen production via different chemical routes: (1) Water-Gas Shift Reaction in membrane reactor, and (2) Thermo-cycle Iodine-Sulphur process.
  • Extractive fed-batch fermentation modeling and novel control strategy based on the MSC Theory.
  • Simplified PID tuning rules for unstable and integrating processes as well as for high-order complex time-delay processes.

Further information on some of their research works can be found in the links below:

SELECTED PUBLICATIONS

  • Nandong and Z. Zang, “High-performance multi-scale control scheme for stable, integrating and unstable time-delay processes,” J. Process Control, vol. 23, pp. 1333-1343, 2013. DOI
  • Nandong and Z. Zang, “Novel multiscale control scheme for Nonminimum-phase processes,” Industrial & Engineering Chemistry Research, vol. 52, pp. 8248-8259, 2013. DOI
  • Nandong and Z. Zang, “Multi-loop design of multi-scale controllers for multivariable processes,” J. Process Control, vol. 24, pp. 600-612, 2014. DOI
  • Nandong and Z. Zang, “Generalized multi-scale control scheme for cascade processes with time-delays,” J. Process Control, vol. 24, pp. 1057-1067, 2014. DOI
  • Nandong and Z. Zang, “Inter-communicative decentralized multi-scale control (ICD-MSC) scheme: a new approach to overcome MIMO process interactions,” Chemical Product & Process Modeling, vol. 9, pp. 165-178, 2014. DOI
  • Nandong, “A unified design for feedback-feedforward control system to improve regulatory control performance,” Int. J. Control, Automation and Systems, vol. 13(1), pp. 1-8, 2015. DOI

 

 

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