Hammerstein Model Based RLS Algorithm for Modeling the Intelligent Pneumatic Actuator (IPA) System
| Autor: | Siti Fatimah Sulaiman, Khairuddin Osman, Ahmad Athif Mohd Faudzi, Mohd. Fua'ad Rahmat, Sy Najib Sy Salim, N. H. Sunar |
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| Rok vydání: | 2017 |
| Předmět: |
Recursive least squares filter
0209 industrial biotechnology Engineering General Computer Science Positioning system Pneumatic actuator business.industry General Engineering System identification Linear model Control engineering 02 engineering and technology Nonlinear system 020901 industrial engineering & automation Computer Science::Systems and Control Control theory 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing General Agricultural and Biological Sciences Actuator business Block (data storage) |
| Zdroj: | International Journal on Advanced Science, Engineering and Information Technology. 7:1457 |
| ISSN: | 2460-6952 2088-5334 |
| Popis: | An Intelligent Pneumatic Actuator (IPA) system is considered highly nonlinear and subject to nonlinearities which make the precise position control of this actuator is difficult to achieve. Thus, it is appropriate to model the system using nonlinear approach because the linear model sometimes not sufficient enough to represent the nonlinearity of the system in the real process. This study presents a new modeling of an IPA system using Hammerstein model based Recursive Least Square (RLS) algorithm. The Hammerstein model is one of the blocks structured nonlinear models often used to model a nonlinear system and it consists of a static nonlinear block followed by a linear block of dynamic element. In this study, the static nonlinear block was represented by a deadzone of the pneumatic valve, while the linear block was represented by a dynamic element of IPA system. A RLS has been employed as the main algorithm in order to estimate the parameters of the Hammerstein model. The validity of the proposed model has been verified by conducting a real-time experiment. All of the criteria as outlined in the system identification’s procedures were successfully complied by the proposed Hammerstein model as it managed to provide a stable system, higher best fit, lower loss function and lower final prediction error than a linear model developed before. The performance of the proposed Hammerstein model in controlling the IPA’s positioning system is also considered good. Thus, this new developed Hammerstein model is sufficient enough to represents the IPA system utilized in this study. |
| Databáze: | OpenAIRE |
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