Author
Woei Wan Tan
Other affiliations: University of Oxford
Bio: Woei Wan Tan is an academic researcher from National University of Singapore. The author has contributed to research in topics: Fuzzy logic & Fuzzy control system. The author has an hindex of 24, co-authored 86 publications receiving 2464 citations. Previous affiliations of Woei Wan Tan include University of Oxford.
Papers published on a yearly basis
Papers
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TL;DR: The book proves to be a valuable resource for professionals seeking to work with fuzzy sets in general and type-2 fuzzy setsIn particular.
Abstract: The book comprises 14 chapters and three appendices. The chapters are organized onto four parts: Preliminaries, Type-1 Fuzzy Logic Systems, Type-2 Fuzzy sets, and Type-2 Fuzzy Logic Systems. The book proves to be a valuable resource for professionals seeking to work with fuzzy sets in general and type-2 fuzzy sets in particular.
313 citations
01 Jun 2008
TL;DR: Results from a simulated coupled tank experiment demonstrated that IT2 FLCs that employ the proposed type reduction algorithm share similar robustness properties as FLC's based on the Karnik-Mendel type reducer.
Abstract: This paper introduces an alternative type-reduction method for interval type-2 (IT2) fuzzy logic systems (FLSs), with either continuous or discrete secondary membership function. Unlike the Karnik-Mendel type reducer which is based on the wavy-slice representation of a type-2 fuzzy set, the proposed type reduction algorithm is developed using the vertical-slice representation. One advantage of the approach is the output of the type reducer can be expressed in closed form, thereby providing a tool for the theoretical analysis of IT2 FLSs. The computational complexity of the proposed method is also lower than the uncertainty bounds method and the enhanced Karnik-Mendel method. To assess the feasibility of the proposed type-reducer, it is used to calculate the output of an IT2 fuzzy logic controller (FLCs). Results from a simulated coupled tank experiment demonstrated that IT2 FLCs that employ the proposed type reduction algorithm share similar robustness properties as FLCs based on the Karnik-Mendel type reducer.
264 citations
TL;DR: Experimental results show that better control can be achieved using a type-2 FLC with fewer fuzzy sets/rules so one benefit of type-1 FLC is a lower trade-off between modeling accuracy and interpretability.
246 citations
25 Jul 2004
TL;DR: Experimental results show that the type-2 FLC copes well with the complexity of the plant, and can handle the modelling uncertainty better than its type-1 counterpart.
Abstract: This paper focuses on evolving type-2 fuzzy logic controllers (FLCs) genetically and examining whether they are better able to handle modelling uncertainties. The study is conducted by utilizing a type-2 FLC, evolved by a genetic algorithm (GA), to control a liquid-level process. A two stage strategy is employed to design the type-2 FLC. First, the parameters of a type-1 FLC are optimized using GA. Next, the footprint of uncertainty is evolved by blurring the fuzzy input set. Experimental results show that the type-2 FLC copes well with the complexity of the plant, and can handle the modelling uncertainty better than its type-1 counterpart.
174 citations
Book•
16 Jun 2014
TL;DR: This key resource will prove useful to students and engineers wanting to learn type-2 fuzzy control theory and its applications.
Abstract: Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students. The coverage provides both background and an extensive literature survey on fuzzy logic and related type-2 fuzzy control. It also includes research questions, experiment and simulation results, and downloadable computer programs on an associated website. This key resource will prove useful to students and engineers wanting to learn type-2 fuzzy control theory and its applications.
171 citations
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TL;DR: This paper demonstrates that it is unnecessary to take the route from general T2 FS to IT2 FS, and that all of the results that are needed to implement an IT2 FLS can be obtained using T1 FS mathematics.
Abstract: To date, because of the computational complexity of using a general type-2 fuzzy set (T2 FS) in a T2 fuzzy logic system (FLS), most people only use an interval T2 FS, the result being an interval T2 FLS (IT2 FLS). Unfortunately, there is a heavy educational burden even to using an IT2 FLS. This burden has to do with first having to learn general T2 FS mathematics, and then specializing it to an IT2 FSs. In retrospect, we believe that requiring a person to use T2 FS mathematics represents a barrier to the use of an IT2 FLS. In this paper, we demonstrate that it is unnecessary to take the route from general T2 FS to IT2 FS, and that all of the results that are needed to implement an IT2 FLS can be obtained using T1 FS mathematics. As such, this paper is a novel tutorial that makes an IT2 FLS much more accessible to all readers of this journal. We can now develop an IT2 FLS in a much more straightforward way
1,892 citations
TL;DR: The Thermophysical Properties Research Literature Retrieval Guide as discussed by the authors was published by Y. S. Touloukian, J. K. Gerritsen and N. Y. Moore.
Abstract: Thermophysical Properties Research Literature Retrieval Guide Edited by Y. S. Touloukian, J. K. Gerritsen and N. Y. Moore Second edition, revised and expanded. Book 1: Pp. xxi + 819. Book 2: Pp.621. Book 3: Pp. ix + 1315. (New York: Plenum Press, 1967.) n.p.
1,240 citations
TL;DR: Digital Control Of Dynamic Systems This well-respected, market-leading text discusses the use of digital computers in the real-time control of dynamic systems with an emphasis on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude.
Abstract: Digital Control Of Dynamic Systems This well-respected, market-leading text discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude. Digital Control of Dynamic Systems (3rd Edition): Franklin ... This well-respected, market-leading text discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude. Digital Control of Dynamic Systems: Gene F. Franklin ... Digital Control of Dynamic Systems, 2nd Edition. Gene F. Franklin, Stanford University. J. David Powell, Stanford University Digital Control of Dynamic Systems, 2nd Edition Pearson This well-respected work discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude. MATLAB statements and problems are thoroughly and carefully integrated throughout the book to offer readers a complete design picture. Digital Control of Dynamic Systems, 3rd Edition ... Digital control of dynamic systems | Gene F. Franklin, J. David Powell, Michael L. Workman | download | B–OK. Download books for free. Find books Digital control of dynamic systems | Gene F. Franklin, J ... Abstract This well-respected work discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic... (PDF) Digital Control of Dynamic Systems Digital Control of Dynamic Systems, Addison.pdf There is document Digital Control of Dynamic Systems, Addison.pdfavailable here for reading and downloading. Use the download button below or simple online reader. The file extension PDFand ranks to the Documentscategory. Digital Control of Dynamic Systems, Addison.pdf Download ... Automatic control is the science that develops techniques to steer, guide, control dynamic systems. These systems are built by humans and must perform a specific task. Examples of such dynamic systems are found in biology, physics, robotics, finance, etc. Digital Control means that the control laws are implemented in a digital device, such as a microcontroller or a microprocessor. Introduction to Digital Control of Dynamic Systems And ... The discussions are clear, nomenclature is not hard to follow and there are plenty of worked examples. The book covers discretization effects and design by emulation (i.e. design of continuous-time control system followed by discretization before implementation) which are not to be found on every book on digital control. Amazon.com: Customer reviews: Digital Control of Dynamic ... Find helpful customer reviews and review ratings for Digital Control of Dynamic Systems (3rd Edition) at Amazon.com. Read honest and unbiased product reviews from our users. Amazon.com: Customer reviews: Digital Control of Dynamic ... 1.1.2 Digital control Digital control systems employ a computer as a fundamental component in the controller. The computer typically receives a measurement of the controlled variable, also often receives the reference input, and produces its output using an algorithm. Introduction to Applied Digital Control From the Back Cover This well-respected, marketleading text discusses the use of digital computers in the real-time control of dynamic systems. The emphasis is on the design of digital controls that achieve good dynamic response and small errors while using signals that are sampled in time and quantized in amplitude. Digital Control of Dynamic Systems (3rd Edition) Test Bank `Among the advantages of digital logic for control are the increased flexibility `of the control programs and the decision-making or logic capability of digital `systems, which can be combined with the dynamic control function to meet `other system requirements. `The digital controls studied in this book are for closed-loop (feedback) Every day, eBookDaily adds three new free Kindle books to several different genres, such as Nonfiction, Business & Investing, Mystery & Thriller, Romance, Teens & Young Adult, Children's Books, and others.
902 citations
TL;DR: In this state-of-the-art paper, important advances that have been made during the past five years for both general and interval type-2 fuzzy sets and systems are described.
614 citations
TL;DR: Methods to reduce their computational cost are proposed in this paper and, on average, the enhanced KM algorithms can save about two iterations, which corresponds to more than a 39% reduction in computation time.
Abstract: The Karnik-Mendel (KM) algorithms are iterative procedures widely used in fuzzy logic theory. They are known to converge monotonically and superexponentially fast; however, several (usually two to six) iterations are still needed before convergence occurs. Methods to reduce their computational cost are proposed in this paper. Extensive simulations show that, on average, the enhanced KM algorithms can save about two iterations, which corresponds to more than a 39% reduction in computation time. An additional (at least) 23% computational cost can be saved if no sorting of the inputs is needed.
505 citations