State Estimation and Control for a Model Scale Passenger Ship using an LQG Approach

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ÇAKICI F., Jambak A. I., Kahramanoğlu E., KARABÜBER A. K., Ustalı B., ÖĞÜR M. U., ...Daha Fazla

Journal of Eta Maritime Science, cilt.12, sa.4, ss.365-376, 2024 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 12 Sayı: 4
  • Basım Tarihi: 2024
  • Doi Numarası: 10.4274/jems.2024.00236
  • Dergi Adı: Journal of Eta Maritime Science
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, Applied Science & Technology Source, Central & Eastern European Academic Source (CEEAS), Directory of Open Access Journals, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.365-376
  • Anahtar Kelimeler: Kalman filter, LQG, Roll stabilization
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Reducing the roll response of ships between irregular waves is an important issue for the operational requirement. This study presents a roll dynamics model for a passenger ship equipped with active fins. In this study, a Kalman Filter was applied to accurately estimate all states from the measurement of total roll motion and roll velocity (based on fins and waves), even in the presence of measurement noise. Synchronously, a linear quadratic gaussian (LQG) controller actively drives the fins to minimize roll motion and velocity by taking the fin amplitude and rate saturations together. Two different sea states were modeled for the simulation purpose. Results demonstrate the success of the state estimation approach and the remarkable potential of the LQG strategy in roll reduction.