Development Of Fuzzv Logic Controllers In Manufacturing Of Resin Adhesives For Wood Industries
Controlling of exothermic reaction in manufacturing of resin adhesives is being performed in chemical industries through human reasoning, expertise and interaction . Human interaction has been a source of control errors which affect the quality of resin product. Since the process of manufacturing of...
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| Format: | Research Report |
| Language: | English English |
| Published: |
2003
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| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/30815/1/Development%20Of%20Fuzzv%20Logic%20Controllers%20In%20Manufacturing%20Of%20Resin%20Adhesives%20For%20Wood%20Industries%20%282%29.pdf https://eprints.ums.edu.my/id/eprint/30815/3/Development%20Of%20Fuzzv%20Logic%20Controllers%20In%20Manufacturing%20Of%20Resin%20Adhesives%20For%20Wood%20Industries.pdf https://eprints.ums.edu.my/id/eprint/30815/ |
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| Summary: | Controlling of exothermic reaction in manufacturing of resin adhesives is being performed in chemical industries through human reasoning, expertise and interaction . Human interaction has been a source of control errors which affect the quality of resin product. Since the process of manufacturing of resin adhesives involves exothermal reaction, automatic control of temperature is very difficult and needs a constant attention by the operator. The exothermic reaction is nonlinear and un-predictably time varying and hence cannot be modeled. Due to this, a PIO control effort is also not suitable. An Artificial Intelligence based control is the only alternative. Since the control law has to be decided amidst unpredictable environment, Fuzzy Logic Control (FLC) can help in making decisions. This is the motivation of this research. A one-step predictor has been designed and include in the FLC loop to compensate the inherent time delay in the process system. The current research substantiates the FLC methodology and proposes further modifications in the fuzzy logic controller in order to overcome some shortfalls of the system such as reduced speed of control and varying steady state errors in temperature responses. The main reason of these shortfalls is due to some . un-measurable parameter of the system that vary slowly and unpredictably. An approach of adaptive control is found appropriate in compensating such parameter variations and is applied as an outer loop to the earlier FLC system. Several experiments performed on this system confirm that the new proposal of adaptive predictive fuzzy logic control is effective in overcoming the shortfalls of predictive fuzr1 logic control system. |
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