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
- 학술대회자료
- 저자정보
- 발행연도
- 2012.10
- 수록면
- 873 - 877 (5page)
이용수
초록· 키워드
오류제보하기
Several methods have been proposed for designing a controller using experimental data directly without identifying a controlled plant. Among them, optimal controller design methods from one-time experimental data, such as Virtual Reference Feedback Tuning (VRFT), Fictitious Reference Iterative Tuning (FRIT), and Noniterative Correlation-based Tuning (NCbT), are especially expected to reduce the time and cost of designing a controller. VRFT and FRIT make a reference signal from experimental data. In contrast, NCbT is a method that removes noise influence by determining parameters for the controller so as not to have the interrelation of the correlation function between a reference signal and noise. However, VRFT and FRIT cannot deal with data that include noises. Although NCbT can be used to design an optimal controller from experimental data with noise, it is limited to cases where there is no interrelation between a reference signal and noise. In this paper, we show a summary of the conventional method and argue about a problem where there is noise. We also propose a data conversion method using linearity after applying spline fitting instead of using experimental data directly. In addition, we discuss the advantages of the conventional method and the proposed method.
목차
Abstract
1. INTRODUCTION
2. CONTROLLER DESIGN METHOD
3. CONTROLLER DESIGN BY PROPOSAL METHOD
4. DATA SMOOTHING BY SPLINE FUNCTION
5. DISCUSSION
6. CONCLUSIONS
REFERENCES
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