A special issue of International Journal of Modelling, Identification and Control
The ability of neural networks and fuzzy logic to represent nonlinear systems is most exploited in the synthesis of nonlinear controllers. One of the main advantages of these techniques is that they do not require the exact determination of a system. This enables these techniques to be used for the design of robust controllers. Further, their abilities to adapt make them suitable to be used for adaptive controllers. This special issue focuses on the promise of artificial neural networks and fuzzy logic in the realm of modelling, identification and control of mechatronic systems.
Original papers reporting new theoretical and experimental development are welcome, including but not limited to the following areas:
- Automotive control
- Magnetic bearing systems
- Vibration monitoring and control
- Robotics
- Control of various manufacturing processes
- Power plant control
- Refrigeration and air conditioning control
- Flow control
- Controls in process plant
Deadline for paper submission: 1st August, 2009
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