Short Bio

Dr. Kayacan  holds a PhD in Electrical and Electronic Engineering from Bogazici University (2011).  He was a visiting scholar in University of Oslo in 2009 with the research fellowship of Norway Research Council. After his post-doctoral research in KU Leuven at the Division of Mechatronics, Biostatistics and Sensors (MeBioS), Dr. Kayacan went on to pursue his research in Nanyang Technological University at the School of Mechanical and Aerospace Engineering as assistant professor (2014 – current).

He has since published more than 100 peer-refereed book chapters, journal and conference papers in intelligent control, artificial intelligence and robotics.  He has attracted around 4 million SGD as principal investigator in the last four years.

Dr. Kayacan is co-writer of a course book “Fuzzy Neural Networks for Real Time Control Applications, 1st Edition Concepts, Modeling and Algorithms for Fast Learning“, Butterworth-Heinemann, Print Book ISBN:9780128026878. (17 Sept 2015).

He is a Senior Member of Institute of Electrical and Electronics Engineers (IEEE). From 1st Jan 2017, he is an Associate Editor of IEEE Transactions on Fuzzy Systems.

News:  Dawn of new era and exciting journey: Dr. Kayacan will be embarking on a new role as Associate Professor at the Department of Engineering at Aarhus University in Denmark.

FUZZ-IEEE is the top leading conference in the area of theory and applications of fuzzy logic.

Let’s meet in Napples, Italy in FUZZ IEEE 2017, 9-12 July 2016 !

This tutorial will consist of two parts:
Part 1: Theoretical framework for type-1 and type-2 FLCs, vision-based control and ROS

1) We will focus on theoretical basis and definitions of type-1 and type-2 FLCs, introduce state-of-art computer vision algorithms for six degree of freedom pose estimation, various commercial applications of UAVs and discuss their limitations and some reasons why FLCs may be useful.
2) We will present a complete computer vision-based control structure of type-1 and type-2 FLCs for navigating UAVs in ROS environment. The main focus will be implementation of type-1 and type-2 FLCs for control of UAVs, and integration of computer vision algorithms and fuzzy controls.
Part 2: Real-Time implementation using ROS
1) We will demonstrate autonomous navigation of UAVs and discuss different fuzzy controller performances. We will also talk about online tuning of FLCs and its advantages under different noisy working conditions.
2) A sample program will be provided so that attendees can explore real-time implementations of UAV control using different FLCs.

FUZZ IEEE 2017 web page: http://www.fuzzieee2017.org/tutorials.html

All codes are available here!

Slides are available here!

New buildings in Singapore may soon have a high-tech building inspector rolling up to their door steps armed with laser scanners and high-tech cameras that can spot the tiniest cracks and defects.

This new building inspector is a robot invented by scientists from Nanyang Technological University, Singapore (NTU Singapore), co-developed with Singapore’s national industrial developer JTC and local start-up CtrlWorks.

Named QuicaBot – short for Quality Inspection and Assessment Robot – it can move autonomously to scan a room in minutes, using high-tech cameras and laser scanners to pick up building defects like cracks and uneven surfaces.

A few of these robots working together will make inspecting a building a breeze. The robots can upload 3D data of the scans to the cloud and inform the human operator, who can then inspect critical and complex defects.

“Visual inspection of a new building is an intensive effort that takes two inspectors, so we have designed a robot to assist a human inspector to do his job in about half the time, saving precious time and manpower, and with great accuracy and consistency,” explained Prof Kayacan.

Reuters: http://www.reuters.com/video/2016/09/26/scientists-create-building-inspection-ro?videoId=369951376

Fuzzy Neural Networks for Real Time Control Applications: Concepts, Modeling and Algorithms for Fast Learning
by Erdal Kayacan and Mojtaba Ahmadieh Khanesar
With foreword by Jerry M. Mendel

AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS

Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book!

Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book.

Google Scholar: http://scholar.google.com.sg/citations?user=50TLpi4AAAAJ&hl=en

ISI ResearcherID: http://www.researcherid.com/rid/D-6256-2014

ResearchGate: http://www.researchgate.net/profile/Erdal_Kayacan