Fuzzy graphic rule network and its application on water bath temperature control system
In this paper, a novel fuzzy neural network called Fuzzy Graphic Rule Network (FGRN) is presented. FGRN has a simple structure and the initial value of its parameters can be easily chosen based on human experience. These parameters are then adjusted during system operation using steepest descent tec...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
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| Online Access: | http://www.scopus.com/inward/record.url?eid=2-s2.0-0036055994&partnerID=40&md5=cb452606d93922f44a3d00d4e2b63aef http://cmuir.cmu.ac.th/handle/6653943832/1416 |
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| Institution: | Chiang Mai University |
| Language: | English |
| Summary: | In this paper, a novel fuzzy neural network called Fuzzy Graphic Rule Network (FGRN) is presented. FGRN has a simple structure and the initial value of its parameters can be easily chosen based on human experience. These parameters are then adjusted during system operation using steepest descent technique. The step length or learning rate is adaptively selected to ensure system stability. As an example, here we employ FGRN as a controller for controlling the temperature of the water bath. Even though the plant's characteristic is highly nonlinear, it is found from the simulation that the FGRN controller can give satisfactory results. |
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