Abstract
A systematic approach to achieving optimal discrete-value harmonic filters using artificial neural network and Taguchi method was developed for a multi-bus system under abundant harmonic current sources. In this simulation, the Taguchi method was used first to perform an efficient experimental design and analyze the robustness of the harmonic filters. Then an artificial neural network (ANN) was used to minimize the variation and make the harmonic filters less sensitive to variations. The L36 orthogonal array was used as the learning data for the ANN to construct an artificial neural network model that could predict the parameters at discrete levels. In the design of harmonic filters, the outer array used to present the noise factors effect of loading uncertainty and changing of system impedances. The searching for optimal solution is applied to the harmonic problems in a steel plant, where both AC and DC arc furnaces are used and a static var compensator (SVC) is installed. The results showed the harmonic filters performance was significantly improved compared with the original design.
| Original language | English |
|---|---|
| Title of host publication | 2006 IEEE International Conference on Mechatronics, ICM |
| Pages | 300-304 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2006 Dec 1 |
| Event | 2006 IEEE International Conference on Mechatronics, ICM - Budapest, Hungary Duration: 2006 Jul 3 → 2006 Jul 5 |
Publication series
| Name | 2006 IEEE International Conference on Mechatronics, ICM |
|---|
Other
| Other | 2006 IEEE International Conference on Mechatronics, ICM |
|---|---|
| Country | Hungary |
| City | Budapest |
| Period | 06-07-03 → 06-07-05 |
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All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering
- Mechanical Engineering
Cite this
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The robust harmonic filter design using artificial neural network and taguchi method. / Chang, Ying Pin; Tseng, Wen Kung.
2006 IEEE International Conference on Mechatronics, ICM. 2006. p. 300-304 4018378 (2006 IEEE International Conference on Mechatronics, ICM).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - The robust harmonic filter design using artificial neural network and taguchi method
AU - Chang, Ying Pin
AU - Tseng, Wen Kung
PY - 2006/12/1
Y1 - 2006/12/1
N2 - A systematic approach to achieving optimal discrete-value harmonic filters using artificial neural network and Taguchi method was developed for a multi-bus system under abundant harmonic current sources. In this simulation, the Taguchi method was used first to perform an efficient experimental design and analyze the robustness of the harmonic filters. Then an artificial neural network (ANN) was used to minimize the variation and make the harmonic filters less sensitive to variations. The L36 orthogonal array was used as the learning data for the ANN to construct an artificial neural network model that could predict the parameters at discrete levels. In the design of harmonic filters, the outer array used to present the noise factors effect of loading uncertainty and changing of system impedances. The searching for optimal solution is applied to the harmonic problems in a steel plant, where both AC and DC arc furnaces are used and a static var compensator (SVC) is installed. The results showed the harmonic filters performance was significantly improved compared with the original design.
AB - A systematic approach to achieving optimal discrete-value harmonic filters using artificial neural network and Taguchi method was developed for a multi-bus system under abundant harmonic current sources. In this simulation, the Taguchi method was used first to perform an efficient experimental design and analyze the robustness of the harmonic filters. Then an artificial neural network (ANN) was used to minimize the variation and make the harmonic filters less sensitive to variations. The L36 orthogonal array was used as the learning data for the ANN to construct an artificial neural network model that could predict the parameters at discrete levels. In the design of harmonic filters, the outer array used to present the noise factors effect of loading uncertainty and changing of system impedances. The searching for optimal solution is applied to the harmonic problems in a steel plant, where both AC and DC arc furnaces are used and a static var compensator (SVC) is installed. The results showed the harmonic filters performance was significantly improved compared with the original design.
UR - http://www.scopus.com/inward/record.url?scp=34250800456&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34250800456&partnerID=8YFLogxK
U2 - 10.1109/ICMECH.2006.252543
DO - 10.1109/ICMECH.2006.252543
M3 - Conference contribution
AN - SCOPUS:34250800456
SN - 0780397134
SN - 9780780397132
T3 - 2006 IEEE International Conference on Mechatronics, ICM
SP - 300
EP - 304
BT - 2006 IEEE International Conference on Mechatronics, ICM
ER -