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Technical Committee on Intelligent Control 
Shuzhi Sam GeDept. of Electrical and Computer Engineering The National University of Singapore Singapore 117576 Phone: 6874 6821 Fax: 6779 1103 elegesz@nus.edu.sg The committee is dedicated to introduce and discuss different topics related to the emerging area of Intelligent Control. Intelligent control, the discipline where control algorithms are developed by emulating certain characteristics of intelligent biological systems, is being fueled by recent advancements in computing technology and is emerging as a technology that may open avenues for significant technological advances.
Research Scope
The ever increasing technological demands of today call for very complex systems, which in turn require highly sophisticated controllers to ensure that high performance can be achieved and maintained under adverse conditions. There are needs in the control of these complex systems, which cannot be met by conventional approaches to control. For instance, there is a significant interest in enhancing current avionic systems so that they can reconfigure the aircraft controls to maintain adequate levels of performance even if there are complete failures in one or more of the actuators or sensors. In a similar manner, there is a significant need to achieve higher degrees of autonomous operation for robotic systems, spacecraft, manufacturing systems, automotive systems, underwater and land vehicles, and others. To achieve such highly autonomous behavior for complex systems one can enhance today's control methods using intelligent control systems and techniques.
The area of Intelligent Control is a fusion of a number of research areas in Systems and Control, Computer Science, and Operations Research among others, coming together, merging and expanding in new directions and opening new horizons to address the problems of this challenging and promising area. Intelligent control systems are typically able to perform one or more of the following functions to achieve autonomous behavior: planning actions at different levels of detail, emulation of human expert behavior, learning from past experiences, integrating sensor information, identifying changes that threaten the system behavior, such as failures, and reacting appropriately. This identifies the areas of Planning and Expert Systems, Fuzzy Systems, Neural Networks, Machine Learning, Multi-sensor Integration, Failure Diagnosis, and Reconfigurable Control, to mention but a few, as existing research areas that are related and important to Intelligent Control. While these techniques provide several key approaches to Intelligent Control, for complex systems they are often interconnected to operate within an architecture which is hierarchical and often distributed. It is for this reason that the areas of hierarchical intelligent control, distributed intelligent control, and architectures for intelligent systems are of significant importance in the design and construction of the overall intelligent controller for complex dynamical systems. Finally, it is of fundamental importance to recognize that (i) intelligent controllers are nonlinear (possibly hierarchical and distributed) controllers that are constructed in nonconventional ways, and (ii) intelligent controllers are often designed to operate in "critical environments" where, for example, the safety of a crew (e.g., in an aircraft/spacecraft), or environmental issues are of concern (e.g., from nuclear power plants or process control). Hence, it is both possible, and of significant importance to introduce mathematical modeling and analysis techniques to be used in the verification and certification of the behavior of intelligent control systems.
Topics of interest
Topics of interest include, but are not limited to:
Techniques for Intelligent Control: Applications / Implementations: |
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