- Tytuł:
- Emotional learning based intelligent speed and position control applied to neurofuzzy model of switched reluctance motor
- Autorzy:
-
Rouhani, H.
Sadeghzadeh, A.
Lucas, C.
Araabi, B. N. - Powiązania:
- https://bibliotekanauki.pl/articles/969753.pdf
- Data publikacji:
- 2007
- Wydawca:
- Polska Akademia Nauk. Instytut Badań Systemowych PAN
- Tematy:
-
intelligent control
emotion based learning
neuro-fuzzy models
switched reluctance motor - Opis:
- In this paper, rotor speed and position of a Switched Reluctance Motor (SRM) are controlled using an intelligent control algorithm. The controller is working based on a PID signal while its gain is permanently tuned by means of an Emotional Learning Algorithm to achieve a better control performance. Here, nonlinear characteristic of SRM is identified using an efficient training algorithm (LoLiMoT) for Locally Linear Neurofuzzy Model as an unspecified nonlinear plant model. Then, the Brain Emotional Learning Based Intelligent Controller (BELBIC) is applied to the obtained model. While the intelligent controller works based on a computational model of a limbic system in the mammalian brain, its contribution is to improve the performance of a classic controller like PID without much more control effort. The results demonstrate excellent improvements of control action in different working situations.
- Źródło:
-
Control and Cybernetics; 2007, 36, 1; 75-95
0324-8569 - Pojawia się w:
- Control and Cybernetics
- Dostawca treści:
- Biblioteka Nauki
Artykuł