LabVIEW based adaptive modeling of piezo actuators used in electro pneumatic positioner
| Autor: | Neville Fernandes, Adwait A. Borwankar, Shilpa Y. Sondkar |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Computer science 020208 electrical & electronic engineering System identification 02 engineering and technology Kalman filter Least mean squares filter Nonlinear system 020901 industrial engineering & automation Data acquisition Control theory Adaptive system 0202 electrical engineering electronic engineering information engineering Actuator Real-time operating system |
| Zdroj: | 2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT). |
| DOI: | 10.1109/icaccct.2016.7831667 |
| Popis: | Piezo actuators are widely use in positioning and control applications. Piezo actuators are nonlinear and possess time varying hysteresis nature. For controlling piezo actuators mostly inverse hysteresis model or adaptive inverse control model are utilize. To implement adaptive inverse control, adaptive model of piezo actuator is to be determined. There are various adaptive methods viz. Recursive Least Square (RLS), Kalman Filter (KF), Least Mean Square (LMS) and Normalized Least Mean Square (NLMS) by which the model can be determined. This paper discusses the system of piezo actuator and different methods of finding adaptive model for piezo actuator system. Further a comparative study of adaptive model identification is carried out and suitable model for this system is identified and discussed. A novel approach of identifying a suitable model is discussed in this paper. The experimentation is carried out using electro pneumatic positioner, which utilizes the piezo valve for positioning. LabVIEW 2014 is used along with data acquisition hardware for modeling of real time system. The results of experimentation shows that, RLS adaptive model is more suitable as compared to other adaptive algorithms. |
| Databáze: | OpenAIRE |
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