| Autor: |
Muhammad Aziz Muslim, Goegoes Dwi Nusantoro |
| Rok vydání: |
2016 |
| Předmět: |
|
| Zdroj: |
2016 International Seminar on Intelligent Technology and Its Applications (ISITIA). |
| Popis: |
As model complexity increased and unknown disturbance introduced, system identification became a useful method to solve necessity of the system model. This paper proposed an auto regressive moving average with exogenous input (ARMAX) structure system identification using Adaptive Neuro-fuzzy Inference System (ANFIS) for a Vacuum distiller. This vacuum distiller is used for bioethanol production. This approach differs from the conventional through the introduction of vacuum pressure disturbance as an exogenous input. Experimental results show that proposed method has comparable performance to the conventional Extended Least Square method. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
