Hybrid adaptive fuzzy control of robot manipulators
Detailed derivations of the Hybrid Adaptive Fuzzy Controller (HAFC) for robot manipulators are included in this thesis. This controller is a weighted combination of DAFC and IAFC together with a continuously-switched supervisory controller. The proposed controller is able to improve the performance...
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sg-ntu-dr.10356-131882023-07-04T16:00:22Z Hybrid adaptive fuzzy control of robot manipulators Chin, Swee Hong. Er, Meng Joo School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Detailed derivations of the Hybrid Adaptive Fuzzy Controller (HAFC) for robot manipulators are included in this thesis. This controller is a weighted combination of DAFC and IAFC together with a continuously-switched supervisory controller. The proposed controller is able to improve the performance of the system in an iterative manner by learning or adapting from the tracking errors that result from previous attempts at achieving the desired motion. In particular, the controller not only does not require the exact mathematical model of the manipulator, but also the boundary of the unknown dynamics can be adaptively estimated on-line. Master of Engineering 2008-08-28T07:23:30Z 2008-10-20T07:18:02Z 2008-08-28T07:23:30Z 2008-10-20T07:18:02Z 1998 1998 Thesis http://hdl.handle.net/10356/13188 en 127 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Chin, Swee Hong. Hybrid adaptive fuzzy control of robot manipulators |
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Detailed derivations of the Hybrid Adaptive Fuzzy Controller (HAFC) for robot manipulators are included in this thesis. This controller is a weighted combination of DAFC and IAFC together with a continuously-switched supervisory controller. The proposed controller is able to improve the performance of the system in an iterative manner by learning or adapting from the tracking errors that result from previous attempts at achieving the desired motion. In particular, the controller not only does not require the exact mathematical model of the manipulator, but also the boundary of the unknown dynamics can be adaptively estimated on-line. |
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Er, Meng Joo |
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Er, Meng Joo Chin, Swee Hong. |
format |
Theses and Dissertations |
author |
Chin, Swee Hong. |
author_sort |
Chin, Swee Hong. |
title |
Hybrid adaptive fuzzy control of robot manipulators |
title_short |
Hybrid adaptive fuzzy control of robot manipulators |
title_full |
Hybrid adaptive fuzzy control of robot manipulators |
title_fullStr |
Hybrid adaptive fuzzy control of robot manipulators |
title_full_unstemmed |
Hybrid adaptive fuzzy control of robot manipulators |
title_sort |
hybrid adaptive fuzzy control of robot manipulators |
publishDate |
2008 |
url |
http://hdl.handle.net/10356/13188 |
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1772825686506995712 |