Online tracking control system for robot manipulator using adaptive fuzzy wavelet network

Abstract EN

It is well known that Wavelet Networks (WN) are powerful tools for handling problems of large dimensions.

The integration of Wavelet Network and Fuzzy Logic (FL) enable a tool condition monitoring system to have a high monitoring success rate and fast training feed over a wide range of cutting conditions in drilling applications.

To overcome offline learning and to perform efficient tracking behavior, an Auto Tuning Adaptive Fuzzy Wavelet Network (ATAFWN) controller is proposed.

It was shown that such structure don’t need offline learning to govern the system in stable regions.

It can be handle also a wide range of parameter changes in comparison with the conventional controller as well as such controller is simple to configure since it doesn’t need a process model and can be easily adapted to the existing controller and plants.