Hybridization of neural and fuzzy systems by a multi agent architecture for motor gearbox control
✍ Scribed by M. Sturm; K. Eder; W. Brauer; J.C. González
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 668 KB
- Volume
- 89
- Category
- Article
- ISSN
- 0165-0114
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✦ Synopsis
In this paper a hybrid system for motor control on testbeds, consisting of neural networks with a self-organizing process state detection and fuzzy rulebases, is proposed. The basic mechanism used for hybridization is a multiagent system composed from loosely interconnected subsystems for the different control tasks to be accomplished• The major aims taken into account are: using standard -and approved -subsystems, realize an easily expandable system, which can handle the exchange or even failure of a component. The proposed system is implemented as a first stage using a simple motor and car simulation. First results show the system's capability to control the car simulation precisely following a given speed profile using knowledge acquisition from the fuzzy system to the neural network. Published by Elsevier Science B.V.