The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Artificial Neural Networks to Improve Current Harmonics Identification and Compensation
|
|
Author(s): Patrice Wira (Université de Haute Alsace, France), Djaffar Ould Abdeslam (Université de Haute Alsace, France)and Jean Mercklé (Université de Haute Alsace, France)
Copyright: 2010
Pages: 35
Source title:
Intelligent Industrial Systems: Modeling, Automation and Adaptive Behavior
Source Author(s)/Editor(s): Gerasimos Rigatos (Industrial Systems Institute & National Technical University of Athens, Greece)
DOI: 10.4018/978-1-61520-849-4.ch010
Purchase
|
Abstract
Artificial Neural Networks (ANNs) have demonstrated very interesting properties in adaptive identification schemes and control laws. In this work, they are employed for the on-line control strategy of an Active Power Filter (APF) in order to improve its performance. Indeed, neural-based approaches are synthesized to design adaptive and efficient harmonic identification schemes. The proposed neural approaches are employed for compensating for the changing harmonic distortions introduced in a power distribution system by unknown nonlinear loads. The implementation of the ANNs has been optimized on a digital signal processor for real-time experiments. The feasibility of the implementation has been validated and the neural compensation schemes exhibit good performances compared to conventional approaches. By their learning capabilities, ANNs are able to take into account time-varying parameters such as voltage sags and harmonic content changes, and thus appreciably improve the performance of the APF compared to the one obtained with traditional compensating methods.
Related Content
|
Poshan Yu, Zixuan Zhao, Emanuela Hanes.
© 2023.
29 pages.
|
|
Subramaniam Meenakshi Sundaram, Tejaswini R. Murgod, Madhu M. Nayak, Usha Rani Janardhan, Usha Obalanarasimhaiah.
© 2023.
20 pages.
|
|
Rekha R. Nair, Tina Babu, Kishore S..
© 2023.
23 pages.
|
|
Wasswa Shafik.
© 2023.
22 pages.
|
|
Jay Kumar Jain, Dipti Chauhan.
© 2023.
24 pages.
|
|
George Makropoulos, Dimitrios Fragkos, Harilaos Koumaras, Nancy Alonistioti, Alexandros Kaloxylos, Vaios Koumaras, Theoni Dounia, Christos Sakkas, Dimitris Tsolkas.
© 2023.
19 pages.
|
|
Shouvik Sanyal, Kalimuthu M., Thangaraja Arumugam, Aruna R., Balaji J., Ajitha Savarimuthu, Chandan Chavadi, Dhanabalan Thangam, Sendhilkumar Manoharan, Shasikala Patil.
© 2023.
17 pages.
|
|
|