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Center of gravity estimation and rollover prevention using Kalman filtering techniques

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dc.contributor Graduate Program in Electrical and Electronic Engineering.
dc.contributor.advisor Akar, Mehmet.
dc.contributor.author Dere, Ali Dinçer.
dc.date.accessioned 2023-03-16T10:17:31Z
dc.date.available 2023-03-16T10:17:31Z
dc.date.issued 2010.
dc.identifier.other EE 2010 D47
dc.identifier.uri http://digitalarchive.boun.edu.tr/handle/123456789/12773
dc.description.abstract Due to its impacts on human safety and its economical cost, vehicle rollover is a very important safety issue that attracts the attention of major vehicle manufacturers and researchers. The objective of this thesis is to design a control system that only becomes active in emergency situations and prevents rollover by applying differential braking to the vehicle. More specifically, the main focus of this thesis is to estimate several unknown vehicle parameters, including the center of gravity height, that has major role in roll over, by using Kalman Filter algorithm. Subsequently, the estimated center of gravity height is used in determining the amount of differential braking force. Extensive simulations are carried out in MATLAB to demonstrate the superior performance of the proposed method.
dc.format.extent 30cm.
dc.publisher Thesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2010.
dc.subject.lcsh Kalman filtering.
dc.subject.lcsh Adaptive control systems.
dc.subject.lcsh Center of mass.
dc.title Center of gravity estimation and rollover prevention using Kalman filtering techniques
dc.format.pages 94 leaves;


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