Intelligent modeling and control of a conveyor belt grain dryer using a simplified type 2 neuro-fuzzy controller
In this article, a nonlinear autoregressive with exogenous input (NARX) network was utilized to model a conveyor belt grain dryer using a set of input–output data collected during an experiment to dry paddy grains. The resulting NARX model has achieved a remarkable modeling accuracy compared to othe...
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| Main Authors: | , , |
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| Format: | Article |
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Taylor and Francis Inc.
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/55995/ http://dx.doi.org/10.1080/07373937.2015.1021007 |
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| Summary: | In this article, a nonlinear autoregressive with exogenous input (NARX) network was utilized to model a conveyor belt grain dryer using a set of input–output data collected during an experiment to dry paddy grains. The resulting NARX model has achieved a remarkable modeling accuracy compared to other previously reported modeling techniques. To control the considered dryer, a simplified type 2 adaptive neuro-fuzzy inference system (ANFIS) controller was proposed. The effectiveness of this controller was demonstrated by several performance tests conducted by computer simulations. Moreover, a comparative study with other related controllers further confirmed the superiority of the proposed dryer controller |
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