2015
DOI: 10.1515/bpasts-2015-0025
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A correction in feedback loop applied to two-axis gimbal stabilization

Abstract: Abstract.A two-axis gimbal system can be used for stabilizing platform equipped with observation system like cameras or different measurement units. The most important advantageous of using a gimbal stabilization is a possibility to provide not disturbed information or data from a measurement unit. This disturbance can proceed from external working conditions. The described stabilization algorithm of a gimbal system bases on a regulator with a feedback loop. Steering parameters are calculated from quaternion t… Show more

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Cited by 6 publications
(6 citation statements)
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“…The radar seeker is employed in the forward-looking mode, as a common practice. Note that the beam is steered to a low-grazing angle area to alleviate the geometry-induced range dependence of clutter in a forward-looking mode [17], and the platform's flight stability is also improved with the stabilization algorithm [18]. The velocity of radar is v a , which is along the X-axis.…”
Section: Geometric Configuration and Multipath-target Signal Modelmentioning
confidence: 99%
“…The radar seeker is employed in the forward-looking mode, as a common practice. Note that the beam is steered to a low-grazing angle area to alleviate the geometry-induced range dependence of clutter in a forward-looking mode [17], and the platform's flight stability is also improved with the stabilization algorithm [18]. The velocity of radar is v a , which is along the X-axis.…”
Section: Geometric Configuration and Multipath-target Signal Modelmentioning
confidence: 99%
“…However, the type of observer is not important in the context of the control system as a whole. There is a possibility to use an observer which estimates the position using any method: using signal injections or the observers, e.g., based on back EMF estimation, using Luenberger and modified Luenberger observers [26], based on various realizations of Kalman filter [27][28][29][30], using sliding mode observers [31][32][33] and artificial neural networks [34]. As mentioned above, the control system utilizes the Luenberger observer.…”
Section: Position Observermentioning
confidence: 99%
“…Naturally, this also involves an extensive volume of literature on filtration [23,24,[28][29][30][31][32][33][34]. The most common types of filters used in this task are: Kalman filter [29,35,36], α-β filter and its extensions [32], and complementary filter [31,35]. The popularity of complementary and α-β filters is due to their simplicity and computational efficiency, which translates into their performance and reduced need for microprocessor power.…”
Section: Introductionmentioning
confidence: 99%