2011
DOI: 10.1080/10798587.2011.10643138
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Ship Course-Keeping Algorithm Based On Knowledge Base

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Cited by 14 publications
(15 citation statements)
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“…U ar = P a + P r -P ar -P ar -1 (5) where P ar is the cross-covariance matrix, calculated recursively with the use of Kalman Filter's matrixes of elementary filters. Such a solution is useless if only estimate and its covariance is known and no more details about elementary filters.…”
Section: Track Fusion Algorithmsmentioning
confidence: 99%
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“…U ar = P a + P r -P ar -P ar -1 (5) where P ar is the cross-covariance matrix, calculated recursively with the use of Kalman Filter's matrixes of elementary filters. Such a solution is useless if only estimate and its covariance is known and no more details about elementary filters.…”
Section: Track Fusion Algorithmsmentioning
confidence: 99%
“…The most important platform for fusion is ECDIS, which is sometimes introduced into INS (Integrated Navigational System). Radar-AIS fusion is also a basis for navigational decision support systems like in [3], [4], [5].…”
Section: Introductionmentioning
confidence: 99%
“…Our considerations will be limited to the class of non-linear single input and affinity systems, due to the form of control signal: = f(x) + g(x)u (2) where: f(x), g(x) -smooth vector fields in R n (infinitely differentiable functions, with a domain and range R n ) and f(0) = 0, u -control signal (scalar).…”
Section: The Controllermentioning
confidence: 99%
“…The above equation can be written as the system: (8) that after the introduction of a Lie derivative [7] takes this form: (9) and accounting for relation (2) and the fact that components: T 2 , ..., T n must be independent of u, contrary to the control v, it will be written as: (10) At this point one can see that the feedback linearization problem actually requires looking for the component T 1 , as later the remaining components T 2 , ..., T n can be determined inductively from the system (10), then the control input (because L g(x) T n (x) ≠ 0): (11) that for: (12) takes the form (3).…”
Section: Feedback Linearization Is Called Global If Dipheomorphism (mentioning
confidence: 99%
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