Computational intelligence method for optimal rotary design system
The application of computational intelligence techniques to the field of industrial robot control is discussed. The core ideas behind using computation, evolutionary computation and fuzzy logic techniques are presented, along with a selection of specific real-world applications. The practical...
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2008
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/7334/1/24p%20KANTAN%20P.SAMINATHAN.pdf http://eprints.uthm.edu.my/7334/2/KANTAN%20P.SAMINATHAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/7334/3/KANTAN%20P.SAMINATHAN%20WATERMARK.pdf |
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| Summary: | The application of computational intelligence techniques to the field of
industrial robot control is discussed. The core ideas behind using computation,
evolutionary computation and fuzzy logic techniques are presented, along with a
selection of specific real-world applications. The practical advantages and
disadvantages relative to more traditional approaches are made clear. The objective
of this project was to investigate and compare different algorithms for the calculation
of velocity from position information. The best algorithm was applied to a small
robot arm system which consists of a controller (PC software), analog-to-digital and
digital-to-analog converter PC card, power amplifier, DC motor, gear train and
external load. Generally in robotic systems a velocity calculation is difficult or
impossible to implement because of noise. Here in the project, fuzzy logic will be
used to filter the noise from the position data before calculating velocity. The
purpose of this research is to design fuzzy logic feedback controller to position the
rotational system with one flexible joint. The system produces oscillations that need
to be dampen. Here the PD (without) controller, ON-OFF controller, Linear
Quadratic Regulator controller (LQR) and Fuzzy Logic controller (sugeno method)
are being used to solve the mentioned oscillatory problem. In order to control the
overall Rotary Flexible Joint System, the Fuzzy Logic controller (FLC) is designed
base upon the coefficients of the existing LQR controller. Comparison between four
controllers was being made through simulation and experiment and the results
showed that the fuzzy controller performed better than the other controllers. |
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