지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국마린엔지니어링학회 Journal of Advanced Marine Engineering and Technology (JAMET) 한국마린엔지니어링학회지 제42권 제2호
- 발행연도
- 2018.2
- 수록면
- 114 - 120 (7page)
- DOI
- 10.5916/jkosme.2018.42.2.114
이용수
초록· 키워드
오류제보하기
Maintaining a constant voltage in a power system is very important for the protection of the electrical and electronic equipment connected to the power system. There are many types of equipment available to keep power quality high, but the most important is an automatic voltage regulator. The control method of an automatic voltage regulator of a synchronous generator is mostly phase control or proportional–integral–derivative (PID) control. However, this paper is compares neural-network predictive control with PID control, and confirms that the proposed neural-network predictive control is effective in adjusting the voltage through experiments conducted by computer simulation.
It is shown that the terminal voltage of the PID control was measured with a rise time of 0.863 s, a settling time of 3.08 s, and an overshoot of 8.23%. The proposed method measured a rise time of 0.58 s, a settling time of 1.02 s, and an overshoot of 0.23%. Through the use of the proposed control method, therefore, the output voltage was improved for 48% of rising time, 3.02 times for the settling time, and 10% in overshoot. In this paper, it is proven that neural-network-predictive control is more effective than PID control in maintaining the constant output voltage of synchronous generators.
It is shown that the terminal voltage of the PID control was measured with a rise time of 0.863 s, a settling time of 3.08 s, and an overshoot of 8.23%. The proposed method measured a rise time of 0.58 s, a settling time of 1.02 s, and an overshoot of 0.23%. Through the use of the proposed control method, therefore, the output voltage was improved for 48% of rising time, 3.02 times for the settling time, and 10% in overshoot. In this paper, it is proven that neural-network-predictive control is more effective than PID control in maintaining the constant output voltage of synchronous generators.
목차
Abstract
1. Introduction
2.Modeling of Synchronous Generator
3. Neural Networks Predictive Control
4. Simulation and result
5. Conclusion
References
참고문헌 (21)
참고문헌 신청
[학술지(정기간행물)] - L. D. S. Coelho / 2009 / Tuning of PID controller for an automatic regulator voltage system using chaotic optimization approach / Chaos, Solitons & Fractals 39 (4) : 1504 ~ 1514
[학술지(정기간행물)] - S. Kansit / 2016 / Optimization of PID controller based on PSOGSA for an automatic voltage regulator system / Procedia Computer Science 86 : 87 ~ 90
[학술지(정기간행물)] - H. Shayeghi / 2015 / Optimal design of a robust discrete parallel FP+FI+FD controller for the Automatic Voltage Regulator system / International Journal of Electrical Power & Energy Systems 67 : 66 ~ 75
[학술지(정기간행물)] - S. Panda / 2012 / Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization / Journal of the Franklin Institute 349 (8) : 2609 ~ 2625
[학술대회논문] - F. Naeim / 2012 / Application of self-tuning PID controller on the AVR system / Proceedings of 2012 IEEE international Conference on Mechatronics and Automation : 2510 ~ 2514
[학술지(정기간행물)] - S. Kansit / 2016 / Optimization of PID controller based on PSOGSA for an automatic voltage regulator system / Procedia Computer Science 86 : 87 ~ 90
[학술지(정기간행물)] - H. Shayeghi / 2015 / Optimal design of a robust discrete parallel FP+FI+FD controller for the Automatic Voltage Regulator system / International Journal of Electrical Power & Energy Systems 67 : 66 ~ 75
[학술지(정기간행물)] - S. Panda / 2012 / Design and performance analysis of PID controller for an automatic voltage regulator system using simplified particle swarm optimization / Journal of the Franklin Institute 349 (8) : 2609 ~ 2625
[학술대회논문] - F. Naeim / 2012 / Application of self-tuning PID controller on the AVR system / Proceedings of 2012 IEEE international Conference on Mechatronics and Automation : 2510 ~ 2514
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