Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence
The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration f...
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Hindawi Limited
2008-01-01
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Series: | Applied Bionics and Biomechanics |
Online Access: | http://dx.doi.org/10.1080/11762320802027869 |
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doaj-4ce9c3d98c0746509b29b0c9823499822021-07-02T03:58:38ZengHindawi LimitedApplied Bionics and Biomechanics1176-23221754-21032008-01-0151334610.1080/11762320802027869Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm IntelligenceAlejandro Carrasco Elizalde0Peter Goldsmith1Department of Mechanical and Manufacturing Engineering, University of Calgary, 2500 University Drive N. W., CanadaDepartment of Mechanical and Manufacturing Engineering, University of Calgary, 2500 University Drive N. W., CanadaThe collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.http://dx.doi.org/10.1080/11762320802027869 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Alejandro Carrasco Elizalde Peter Goldsmith |
spellingShingle |
Alejandro Carrasco Elizalde Peter Goldsmith Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence Applied Bionics and Biomechanics |
author_facet |
Alejandro Carrasco Elizalde Peter Goldsmith |
author_sort |
Alejandro Carrasco Elizalde |
title |
Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence |
title_short |
Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence |
title_full |
Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence |
title_fullStr |
Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence |
title_full_unstemmed |
Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence |
title_sort |
adaptive fuzzy-lyapunov controller using biologically inspired swarm intelligence |
publisher |
Hindawi Limited |
series |
Applied Bionics and Biomechanics |
issn |
1176-2322 1754-2103 |
publishDate |
2008-01-01 |
description |
The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language. |
url |
http://dx.doi.org/10.1080/11762320802027869 |
work_keys_str_mv |
AT alejandrocarrascoelizalde adaptivefuzzylyapunovcontrollerusingbiologicallyinspiredswarmintelligence AT petergoldsmith adaptivefuzzylyapunovcontrollerusingbiologicallyinspiredswarmintelligence |
_version_ |
1721340897052852224 |