Browse Topic: Fuzzy logic

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In-phase rear-wheel steering, where rear wheels are steered in the same direction of front wheels, has been widely investigated in the literature for vehicle stability improvements along with stability control systems. Much faster response can be achieved by steering the rear wheels automatically during an obstacle avoidance maneuver without applying the brakes where safe stopping distance is not available. Sudden lane change movements still remain challenging for heavy articulated vehicles, such as tractor and semitrailer combinations, particularly on roads with low coefficient of adhesion. Different lateral accelerations acting on tractor and semi-trailer may cause loss of stability resulting in jackknifing, trailer-swing, rollover, or slip-off. Several attempts have been made in the literature to use active steering of semi-trailer’s rear wheels to prevent jackknifing and rollover. However, loss of stability in an articulated vehicle is usually caused by an oversteered tractor, and
Sahin, HasanAkalin, Ozgen
A redundant strap-down attitude system using three miniaturized gyro sensors linear clusters in the detection unit are here presented. For each of the three clusters the inertial sensors' data are fused by using a fuzzy logic method, in order to improve the angular speed signal measured by the detection unit and delivered to the attitude algorithm. After a short introduction the data fusion algorithm and the theoretical background of the attitude system are shown in the sections two and three. In the fourth section, the software implementation and experimental validation of the redundant inertial attitude system are exposed. To perform the experimental validation of the developed redundant attitude system some data were simultaneously acquired from a three-dimensional redundant gyro sensors unit and from an integrated INS/GPS navigator; the INS/GPS system was used as reference system to perform an evaluation of the attitude angles errors. The three-dimensional redundant gyro sensors
Sandu, DragosGrigorie, TeodorBotez, Ruxandra
Simple and effective learning functions and adaptive elements can be placed into small hardware systems to include instruments for space, bioimplantable devices, and stochastic observers.
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