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INTERNATIONAL JOURNAL OF

SYSTEMS SCIENCE

SPECIAL ISSUE CALL FOR PAPERS

INTERVAL TYPE-2 FUZZY-MODEL-BASED CONTROL DESIGN AND MEMBERSHIP-FUNCTIONS-DEPENDENT ANALYSIS

Guest Editors

Bo Xiao (Imperial College London), Hak-Keung Lam (King’s College London), Sakthivel Rathinasamy (Bharathiar University) & Radu-Emil Precup (Politehnica University of Timisoara).

Summary and Scope

As a recent research hot spot in the fuzzy control field, the Interval Type-2 (IT2) Fuzzy-Model-Based (FMB) control design has demonstrated its capacity in handling the uncertainties in nonlinear control systems directly. Within the IT2 control design framework, the uncertainties considered can be parameters uncertainty, mismeasurement uncertainty, observation uncertainty, communication uncertainty, etc. The first successful attempt on the stability analysis of FMB control systems subject to parameter uncertainty was conducted by Dr. H.K. Lam in 2008 (Lam, H.K. and Seneviratne, L.D., 2008. Stability analysis of interval type-2 fuzzy-model-based control systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 38(3), pp.617-628). In this work, Dr.Lam has demonstrated that IT2 membership functions can be effectively utilized to include the parameter uncertainty into the stability analysis and conditions. Thus, the stability conditions are valid for all the possible parameters within certain parameter ranges. Since then, there were follow-up works utilizing IT2 fuzzy sets to deal with the control design of nonlinear systems subject to uncertainty. Besides, when the membership functions of the fuzzy model and controller are different in the number of rules or/and shapes, the mismatch issue of membership functions occurs. In this case, the parallel distributed compensation (PDC) approach cannot be applied to relax the stability conditions since it demands the perfect match of the membership functions of the fuzzy model and controller. In addition, the mismatch of membership functions of the fuzzy model and controller has been observed even when the membership functions are intended to be designed as exactly the same in some specific control mechanisms, such as the sampled-data control design, networked control design, etc. Along the membership-function-dependent (MFD) approaches with the imperfect premise matching (IPM) concept, the IT2 FMB control strategies were adopted to address the mismatch issue of the premise variables of the fuzzy model and controller. Since the mismatch of premise variables is considered in the analysis, the obtained stability conditions are more rigorous.

 

During the past decade, researchers gradually recognized the importance and necessity of utilizing IT2 fuzzy sets in the FMB control design. Although there were already some seminal works on IT2 FMB control systems that can be found in the literature, there are still many interesting related topics await.

 

The potential research topics for IT2 FMB control systems can be the relaxation of stability conditions through MFD approaches, different control design methodologies, addressing the specific issues in fuzzy control systems along with the IT2 design, applications of IT2 fuzzy control to physical systems, etc. The list of possible topics includes, but is not limited to:

  • Relaxation of stability conditions through MFD approaches;

  • New stability conditions of IT2 FMB control systems;

  • IT2 modeling of nonlinear systems subject to uncertainty;

  • Addressing the mismatch issue of membership functions within the IT2 framework;

  • Adaptive and optimal control design for IT2 FMB control systems;

  • Networked IT2 FMB control design;

  • IT2 fuzzy neural-network control systems;

  • Stability/performance/robustness analysis of IT2 FMB control system;

  • Improve the IT2 fuzzy controller through data-driven techniques;

  • Optimize the IT2 fuzzy controller through machine learning techniques;

  • Applications of IT2 FMB control strategy to unmanned aerial vehicles;

  • Applications of IT2 FMB control strategy to robotics.


Submission Guidelines

Authors should prepare their manuscripts according to the "Instructions for Authors" guidelines of International Journal of Systems Science outlined at the journal website. All papers will be peer-reviewed following a regular reviewing procedure. Each submission should clearly demonstrate evidence of benefits to society or large communities. Originality and impact on society, in combination with a media-related focus and innovative technical aspects of the proposed solutions will be the major evaluation criteria.

During the submission process, please do the following:

  • On Step 1 select"Special Issue" as the article type.

  • On Step 6 select "IT2 FMB" when asked which special issue your manuscript is for.

 

Important Dates

  • Submission Deadline: 31 December 2020

  • First Review Decision: 1 March 2021

  • Revisions Due: 1 May 2021

  • Final Manuscript: 1 July 2021

  • Expected publication date: Summer/Autumn 2021

Guest Editors

Dr. Bo Xiao, Imperial College London, email: b.xiao@imperial.ac.uk

Short Bio:

Dr. Bo Xiao received Ph.D. degree from the Department of Informatics, King’s College London, U.K. in 2018. He is currently a research associate with Hamlyn Centre for Robotic Surgery and the Department of Computing, Imperial College London, U.K. During the period 2017 to 2018, he worked as a research fellow at Advanced Robotics Centre and the Department of Biomedical Engineering, National University of Singapore, Singapore. His current research interests include fuzzy-model-based control systems, interval type-2 fuzzy logic, polynomial control systems, machine learning, reinforcement learning and their applications in medical robotics.

 

He has been the guest editor for IEEE Transactions on Fuzzy Systems, IET Control Theory and Applications, and Mathematical Problems in Engineering. He has served as an active reviewer for a number of peer-reviewed journals including IEEE Transactions on Fuzzy Systems, IEEE Transactions on Automatic Control, IEEE Transactions on Cybernetics, Fuzzy Sets and Systems and IET Control Theory and Applications.

Publications:

  1. Xiao, B., Lam, H.K. and Li, H., 2016. Stabilization of interval type-2 polynomial-fuzzy-model-based control systems. IEEE Transactions on Fuzzy Systems, 25(1), pp.205-217.

  2. Xiao, B., Lam, H.K., Yu, Y. and Li, Y., 2019. Sampled-data output-feedback tracking control for interval type-2 polynomial fuzzy systems. IEEE Transactions on Fuzzy Systems, 28(3), pp.424-433.

  3. Xiao, B., Lam, H.K., Zhong, Z. and Wen, S., 2019. Membership-Function-Dependent Stabilization of Event-Triggered Interval Type-2 Polynomial Fuzzy-Model-Based Networked Control Systems. IEEE Transactions on Fuzzy Systems.

  4. Xiao, B., Lam, H.K., Zhou, H. and Gao, J., 2020. Analysis and Design of Interval Type-2 Polynomial-Fuzzy-Model-Based Networked Tracking Control Systems. IEEE Transactions on Fuzzy Systems.

  5. Xiao, B., Lam, H.K., Song, G. and Li, H., 2017. Output-feedback tracking control for interval type-2 polynomial fuzzy-model-based control systems. Neurocomputing, 242, pp.83-95.

 

 

Dr. Hak-Keung Lam, King’s College London, email: hak-keung.lam@kcl.ac.uk

Short Bio:

Dr. H. K. Lam received the B.Eng. (Hons.) and Ph.D. degrees from the Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, in 1995 and 2000, respectively. During the period of 2000 and 2005, he worked with the Department of Electronic and Information Engineering at The Hong Kong Polytechnic University as Post-Doctoral Fellow and Research Fellow respectively. He joined as a Lecturer at King’s College London in 2005 and is currently a Reader.

 

His current research interests include intelligent control and computational intelligence. He has served as a program committee member, international advisory board member, invited session chair and publication chair for various international conferences and a reviewer for various books, international journals and international conferences. He is an associate editor for IEEE Transactions on Fuzzy Systems, IET Control Theory and applications, International Journal of Fuzzy Systems, Neurocomputing, and Nonlinear Dynamics; and was an associate editor for IEEE Transactions on Circuits and Systems II: Express Briefs. He was guest editor and on the editor board for many international journals.

 

He is a co-editor of two edited volumes: Control of Chaotic Nonlinear Circuits (World Scientific, 2009) and Computational Intelligence and Its Applications (World Scientific, 2012), and author/coauthor of three monographs: Stability Analysis of Fuzzy-Model-Based Control Systems (Springer, 2011), Polynomial Fuzzy Model Based Control Systems (Springer, 2016) and Analysis and Synthesis for Interval Type-2 Fuzzy-Model-Based Systems (Springer, 2016).

 

He was named in Highly Cited Researchers 2018 and 2019 lists. Extracted from the Highly Cited Researchers 2018 list, it states that “This list recognizes world-class researchers selected for their exceptional research performance, demonstrated by production of multiple highly cited papers that rank in the top 1% by citations for field and year in Web of Science”. He is an IEEE fellow.

Publications:

  1. Lam, H.K. and Seneviratne, L.D., 2008. Stability analysis of interval type-2 fuzzy-model-based control systems. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 38(3), pp.617-628.

  2. Lam, H.K., Li, H., Deters, C., Secco, E.L., Wurdemann, H.A. and Althoefer, K., 2013. Control design for interval type-2 fuzzy systems under imperfect premise matching. IEEE Transactions on Industrial Electronics, 61(2), pp.956-968.

  3. Lam, H.K. and Narimani, M., 2008. Stability analysis and performance design for fuzzy-model-based control system under imperfect premise matching. IEEE Transactions on Fuzzy Systems, 17(4), pp.949-961.

  4. Lam, H.K. and Narimani, M., 2009. Quadratic-stability analysis of fuzzy-model-based control systems using staircase membership functions. IEEE Transactions on Fuzzy Systems, 18(1), pp.125-137.

  5. Lam, H.K., 2011. Polynomial fuzzy-model-based control systems: stability analysis via piecewise-linear membership functions. IEEE Transactions on Fuzzy Systems, 19(3), pp.588-593.

 

 

Dr. Sakthivel Rathinasamy, Bharathiar University, email: krsakthivel0209@gmail.com

Short Bio:

R. Sakthivel received the B.Sc., M.Sc., M.Phil., and Ph.D. degrees in mathematics from Bharathiar University, Coimbatore, India, in 1992, 1994, 1996, and 1999, respectively. He was a Lecturer with the Department of Mathematics, Sri Krishna College of Engineering and Technology, Coimbatore, from 2000 to 2001. From 2001 to 2003, he was a Post-Doctoral Fellow with the Department of Mathematics, Inha University, Incheon, South Korea. He was a Visiting Fellow with the Max Planck Institute, Magdeburg, Germany, in 2002. From 2003 to 2005, he was a Japan Society for the Promotion of Science Fellow with the Department of Systems Innovation and Informatics, Kyushu Institute of Technology, Kitakyushu, Japan. He was a Research Professor with the Department of Mathematics, Yonsei University, Seoul, South Korea, until 2006. He was a Post-Doctoral Fellow (Brain Pool Program) with the Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, South Korea, from 2006 to 2008. He was an Assistant Professor and an Associate Professor with the Department of Mathematics, Sungkyunkwan University, Suwon, South Korea, from 2008 to 2013. From 2013 to 2016, he was a Professor at the Department of Mathematics, Sri Ramakrishna Institute of Technology, India. He is currently a Professor with the Department of Applied Mathematics, Bharathiar University, Coimbatore, India. He has served as a program committee member, and a reviewer for various books, international journals and international conferences. His current research interests include systems and control theory, and nonlinear dynamical systems.  He has been on the editorial board of international journals, including the IEEE Access, Journal of the Franklin Institute, Neurocomputing, Neural Processing Letters, Advances in Difference equations, and the Journal of Electrical Engineering

and Technology. He was named in Highly Cited Researchers 2017, 2018 and 2019 list.

Publications:

  1. Kavikumar,R., Sakthivel, R., Kwon.O.M. and Kaviarasan, B., 2020. Robust model reference tracking control for interval type-2 fuzzy stochastic systems. IET Control Theory & Applications, 14(9), pp.1123-1134.

  2. Sakthivel, R., Raajananthini., Kwon, O.M. and Mohanapriya, S., 2019. Estimation and disturbance rejection performance for fractional order fuzzy systems. ISA transactions, 92, pp.65-74.

  3. Sakthivel, R.,Kaviarasan, B., Selvaraj, P. and Karimi, H.R., 2019. EID-based sliding mode investment policy design for fuzzy stochastic jump financial systems. Nonlinear Analysis: Hybrid Systems, 31, pp.100-108.

  4. Sakthivel, R., Karthick.S.A, Kaviarasan, B. and Alzahrani, F., 2018. Dissipativity-based non-fragile sampled-data control design of interval type-2 fuzzy systems subject to random delays. ISA transactions, 83, pp.154-164.

  5. Kavikumar,R., Sakthivel, R., Kwon.O.M. and Kaviarasan, B., 2019. Finite-time boundedness of interval type-2 fuzzy systems with time delay and actuator faults. Journal of the Franklin Institute, 356 (15), pp.8296-8324.

Prof. Radu-Emil Precup, Politehnica University of Timisoara, email: radu.precup@aut.upt.ro

Short Bio:

Prof. R.-E. Precup received the Dipl.Ing. (Hons.) degree in automation and computers from the "Traian Vuia" Polytechnic Institute of Timisoara, Timisoara, Romania, in 1987, the Diploma in mathematics from the West University of Timisoara, Timisoara, in 1993, and the Ph.D. degree in automatic systems from the "Politehnica" University of Timisoara, Timisoara, in 1996. From 1987 to 1991, he was with Infoservice S.A., Timisoara. He is currently with the Politehnica University of Timisoara, Romania, where he became a Professor in the Department of Automation and Applied Informatics, in 2000, and he is currently a Doctoral Supervisor of automation and systems engineering. He is also an Adjunct Professor within the School of Engineering, Edith Cowan University, Joondalup, WA, Australia, and an Honorary Professor and a Member of the Doctoral School of Applied Informatics with the Óbuda University (previously named Budapest Tech Polytechnical Institution), Budapest, Hungary. He is currently the Director of the Automatic Systems Engineering Research Centre with the Politehnica University of Timisoara, Romania. From 1999 to 2009, he held research and teaching positions with the Université de Savoie, Chambéry and Annecy, France, Budapest Tech Polytechnical Institution, Budapest, Hungary, Vienna University of Technology, Vienna, Austria, and Budapest University of Technology and Economics, Budapest, Hungary. He has been an Editor-in-Chief of the International Journal of Artificial Intelligence since 2008 and he is also on the editorial board of several other prestigious journals including IEEE Transactions on Fuzzy Systems, IEEE Transactions on Cybernetics, Information Sciences (Elsevier), Applied Soft Computing (Elsevier), Evolving Systems (Springer) and Cogent Engineering (Taylor & Francis).

 

He is the author or coauthor of more than 300 papers published in various scientific journals, refereed conference proceedings, and contributions to books. His research interests include mainly development and analysis of new control structures and algorithms (conventional control, fuzzy control, data-based control, sliding mode control, neuro-fuzzy control, etc.), theory and applications of soft computing, computer-aided design of control systems, modelling, optimization (including nature-inspired algorithms), and applications to mechatronic systems (including automotive systems and mobile robots), embedded systems, control of power plants, servo systems, electrical driving systems.

 

Prof. Precup is a corresponding member of The Romanian Academy, a member of the Subcommittee on Computational Intelligence as part of the Technical Committee (TC) on Control, Robotics and Mechatronics in the Institute of Electrical and Electronics Engineers (IEEE) Industrial Electronics Society, the Task Force on Autonomous Learning Systems within the Neural Networks TC of the IEEE Computational Intelligence Society, the TCs on Computational Cybernetics and Cyber-Medical Systems of the IEEE Systems, Man, and Cybernetics Society, the Task Force on Adaptive and Evolving Fuzzy Systems within the Fuzzy Systems Technical Committee of the IEEE Computational Intelligence Society, the International Federation of Automatic Control (IFAC) Technical Committee on Computational Intelligence in Control (previously named Cognition and Control), the Working Group WG 12.9 on Computational Intelligence of the Technical Committee TC12 on Artificial Intelligence of the International Federation for Information Processing (IFIP), the European Society for Fuzzy Logic and Technology (EUSFLAT), the Hungarian Fuzzy Association, and the Romanian Society of Control Engineering and Technical Informatics.

 

He was the recipient of the Elsevier Scopus Award for Excellence in Global Contribution (2017), the "Grigore Moisil" Prize from the Romanian Academy, two times, in 2005 and 2016, for his contribution on fuzzy control and the optimization of fuzzy systems, the Spiru Haret Award from the National Grand Lodge of Romania in partnership with the Romanian Academy in 2016 for education, environment and IT, the Excellency Diploma of the International Conference on Automation, Quality & Testing, Robotics AQTR 2004 (THETA 14, Cluj-Napoca, Romania), two Best Paper Awards in the Intelligent Control Area of the 2008 Conference on Human System Interaction HSI 2008, Krakow (Poland), the Best Paper Award of 16th Online World Conference on Soft Computing in Industrial Applications WSC16 (Loughborough University, UK) in 2011, the Certificate of Appreciation for the Best Paper in the Session TT07 1 Control Theory of 39th Annual Conference of the IEEE Industrial Electronics Society IECON 2013 (Vienna, Austria), a Best Paper Nomination at 12th International Conference on Informatics in Control, Automation and Robotics ICINCO 2015 (Colmar, France), a Best Paper Award at 7th International Conference on Information Technology and Quantitative Management ITQM 2019 (Granada, Spain), and was listed as one of the top 10 researchers in Artificial Intelligence and Automation (according to IIoT World as of July 2017).

 

Publications:

  1. R.-E. Precup and H. Hellendoorn, A survey on industrial applications of fuzzy control, Computers in Industry, vol. 62, no. 3, pp. 213-226, 2011.

  2. R.-E. Precup, R.-C. David and E. M. Petriu, Grey wolf optimizer algorithm-based tuning of fuzzy control systems with reduced parametric sensitivity, IEEE Transactions on Industrial Electronics, vol. 64, no. 1, pp. 527-534, 2017.

  3. R.-E. Precup, M.-B. Radac, R.-C. Roman and E. M. Petriu, Model-free sliding mode control of nonlinear systems: algorithms and experiments, Information Sciences, vol. 381, pp. 176-192, 2017.

  4. R.-E. Precup, R.-C. David, E. M. Petriu, M.-B. Radac, S. Preitl and J. Fodor, Evolutionary optimization-based tuning of low-cost fuzzy controllers for servo systems, Knowledge-Based Systems, vol. 38, pp. 74-84, 2013.

  5. R.-E. Precup, P. Angelov, B. S. J. Costa and M. Sayed-Mouchaweh, An overview on fault diagnosis and nature-inspired optimal control of industrial process applications, Computers in Industry, vol. 74, pp. 75-94, 2015.