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 80 peer-refereed book chapters, journal and conference papers in intelligent control, fuzzy systems and robotics.  He has attracted around 4 million SGD as principal investigator in the last three years. His current research projects focus on the design and development of ground and aerial robotic systems, vision-based control techniques and  artificial intelligence. 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.

A new tutorial in FUZZ-IEEE 2017: Vision-Based Control of UAVs Using Type-1 and Type-2 FLCs with ROS


NEWS: 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 !

As a model-free control technique, type-1 and type-2 fuzzy logic controllers (FLCs) have already been implemented in many industrial control systems. However, they still lack in real-time implementations for UAVs, especially for type-2 FLCs. Therefore, the main aim of this tutorial is to discuss and present real-time implementations of type-1 and type-2 FLCs for controlling UAVs.

This tutorial will consist of two parts:
Part 1: Theoretical framework for type-1 and type-2 FLCs, vision-based control and ROSms-ho-ching-visit-0163-wa
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:

All codes are available here!

Slides are available here!

FUZZ IEEE 2017 Tutorial

Media Release of Quicabot

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.img_0860

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.


A new book in adaptive neuro-fuzzy systems is available!


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


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.

Projects Directed

  • ST Eng-NTU Corp Lab
    ST Eng-NTU Corp Lab: Precise landing for unmanned aerial vehicles
    470,000SGD by ST Eng-NTU Corp Lab
  • ST Eng-NTU Corp Lab
    ST Eng-NTU Corp Lab: Fuzzy neural network-based learning control of unmanned aerial vehicles
    130,000SGD by ST Eng-NTU Corp Lab
  • JTC Corporation - NRF
    JTC Corporation - NRF: Automated Construction Quality Assessment Robot System (A-CONQUARS)
    821,160SGD by JTC Corporation - NRF
  • NTU Start up Grant
    NTU Start up Grant (Learning control algorithms for unmanned aerial vehicles)
    100,000SGD by Nanyang Technological University
  • MOE Tier 1
    MOE Academic Research Funding (AcRF) Tier 1: Model predictive control-moving horizon estimation framework as applied to tilt rotor UAVs and its experimental evaluation
    88,000SGD by Nanyang Technological University
  • NRF
    NRF - Design of lightweight UAV for 3D Printing
    2,052,500SGD by NRF Medium-Sized Centre (MSC)

Publication Database

Citations Map: displays geographic locations for publications that have cited me. (From ISI ResearcherID)

Screen Shot 2016-08-11 at 11.42.01 AM

Collaborators Map: displays geographic locations for my collaborators. (From ISI ResearcherID)

Screen Shot 2016-08-11 at 11.43.05 AM