In this paper we derive a state variable estimation method of discrete stochastic dynamical systems. It aims to obtain accurate estimation with short computing time. Therefore, the point of this paper is to discuss a construction of Kalman filter algorithm on the reduced model. First, we construct a reduced model by using balanced truncation method. Further, we apply state variable estimation steps of discrete stochastic dynamical systems by using Kalman filter on the reduced model. Thus, Kalman filter algorithm will be constructed on the reduced model.
목차
Abstract 1. Introduction 2. The Algorithm of Kalman Filter on the Discrete System 3. Reduced Model Construction on the Discrete Systems 4. The Algorithm of Kalman Filter on the Reduced Model 5. Case study 6. Conclusions Acknowledgements References
키워드
estimationKalman filterbalanced systemreduced model
저자
Didik Khusnul Arif [ Post Graduate Student in Department of Mathematics, Universitas Gadjah Mada (UGM), Yogyakarta, Indonesia, Department of Mathematics, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia. ]
Widodo [ Department of Mathematics, Universitas Gadjah Mada (UGM), Yogyakarta, Indonesia. ]
Salmah [ Department of Mathematics, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia. ]
Erna Apriliani [ Department of Mathematics, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia. ]
보안공학연구지원센터(IJCA) [Science & Engineering Research Support Center, Republic of Korea(IJCA)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Control and Automation
간기
월간
pISSN
2005-4297
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Control and Automation Vol.7 No.9