Design of unknown inputs robust fuzzy observer for lane departure detection Online publication date: Fri, 10-Apr-2015
by Mohammed Chadli; Hamid Dahmani; H. Dahmani; M. Chadli; A. Rabhi; A. El Hajjaji
International Journal of Vehicle Design (IJVD), Vol. 56, No. 1/2/3/4, 2011
Abstract: A lane departure detection method is proposed using Takagi-Sugeno (T-S) fuzzy approach in this paper. To deal with this problem, a nonlinear model deduced from a vehicle lateral dynamic and a vision system is represented by an uncertain T-S fuzzy model affected by unknown inputs. The developed lane departure detection technique is based on an unknown inputs fuzzy observer. Design conditions of such observers are expressed in terms of Linear Matrix Inequalities (LMI). Indeed, the road curvature considered as unknown input is estimated and compared to the vehicle trajectory curvature. The proposed algorithm allows to reduce false alarms and to integrate the driver corrections by taking the steering dynamics into account. In order to show the ef?ciency of the given method, simulations with different driving scenarios are proposed.
Online publication date: Fri, 10-Apr-2015
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