Prasanth wrote:In recent years, intelligent control has emerged as one of the most active and fruitful areas of research and development. Intelligent systems are usually described by analogies with biological systems by, for example, looking at how human beings perform control tasks, recognize patterns, or make decisions. Such area is a fusion of systems and control, computer science and operations research. Intelligent control systems are typically able to perform one or more of the following functions: planning actions at different levels, learning from past experience, identifying changes against the system behavior, such as performance degradation, failures, cross-coupling and then reacting appropriately. The field of intelligent control has been applied to modern industrial systems, which are under dominance by diverse technical spheres of knowledge, specially containing mechanical, electrical, hydraulic, control system and drive train devices, where large models are required. To keep up the driving technology, engineers need to build systems orders of magnitude more complex than previous ones and deploy them faster. Therefore, intelligent control techniques are important for dealing with complex systems under such a new paradigm. This paper will focus on neural networks and fuzzy logic applications into the design of control systems.
TECHNIQUES FOR INTELLIGENT CONTROL
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.