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TC 3.2. Computational Intelligence in Control


Since decades now, a part of Automatic control has been put under the general appellation of “intelligent control” which definition is very difficult to give, as it is a kind of umbrella covering various different methodologies. The TC 3.2 “Computational Intelligence in Control” groups some of the major manifestations of these methodologies including, fuzzy, neural (both artificial and biologically plausible), linguistic, fuzzy-neural, evolutionary, reinforcement learning… approaches. As related and applied to automatic control, it covers modeling, identification, forecasting, stability/stabilization analysis, diagnosis, fault detection, design, learning, adaptation, evaluation, definition of performances objectives and operation constraints, as well as awareness for computational issues, brain-computer interfacing, bioinformatics and computer-aided design tools.


Generally, the approaches differ from the conventional approaches in control and one of the goals is to cope with problems – especially industrial ones – where conventional methods were proved unsuccessful. Applications include transport, medical and biomedical, biology, aerospace, automation, biotechnology, mechatronics, automation, manufacturing, process control, power systems, energy and smart grid, agriculture, environmental systems, robotics and autonomous systems, economics and business systems.


Nowadays, there are many communities that belong to the area of Computational Intelligence. The TC 3.2 has to be active and to promote the activities related to control in a broad sense in order to impact the IFAC community and to become a recognized international community of leading practitioners and researchers in this area.


As re-elected chair for the triennium 2017 – 2020 of this committee and together with the well established vice-chairs, we welcome all the initiatives in order to achieve these goals and promote our community.


TC 3.2. Computational Intelligence in Control

Welcome Message from the Chair

Welcome to the homepage of the IFAC Technical Committee on Computational Intelligence in Control, TC 3.2.



These pages collect details of technical activities sponsored by IFAC in the area of Computational Intelligence, together with related information and links likely to be of interest to researchers and practicing engineers.


TC 3.2 focuses on all aspects of knowledge-based, fuzzy, neuro-fuzzy and neural (both artificial and biologically plausible) systems and evolutionary algorithms relevant to control, both theoretically and application driven.


Our membership lists more than 50 people (please see TC Roster) and we would be glad to meet you as active researcher in one of our conferences.


How to join


To become a member of the TC 3.2, you have several possibilities:

  • Being nominated by your National Member Organization.
  • Write a letter to the IFAC Secretariat + CV, that will be forwarded the Chair of the Committee.
  • Contact directly the chair of the Technical Committee


Individual involvement in IFAC


Anyone interested in Control Engineering may become an IFAC Affiliate. IFAC Affiliates receive the IFAC Newsletter free of charge. The Newsletter contains information about IFAC technical meetings as well as about other matters of interest to the control community. IFAC Affiliates will also receive Calls for Papers for technical meetings in their selected areas of interest and are entitled to a special rate for subscriptions to the IFAC Journals Automatica, Control Engineering Practice, Annuals Review in Control, Journal of Process Control, Engineering Applications of Artificial Intelligence.

You can register as an IFAC Affiliate using the on-line registration form.

Thierry Marie Guerra

Thierry Marie Guerra
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