Vehicle dynamics and road geometry estimation using a Takagi-Sugeno fuzzy observer with unknown inputs

Abstract

This paper describes a methodology for estimating both vehicle dynamics and road geometry using a Fuzzy unknown input observer. Vehicle sideslip and roll parameters are estimated in presence of the road bank angle and the road curvature as unknown inputs. The unknown inputs are then estimated using the observer results. The used nonlinear model deduced from the vehicle lateral and roll dynamics with a vision system is represented by a Takagi-Sugeno (TS) fuzzy model in order to take into account the nonlinearities of the cornering forces. Taking into account the unmeasured variables, an unknown inputs (TS) observer is then designed on the basis of the measure of the roll rate, the steering angle and the lateral offset given by the distance between the road centerline and the vehicle axe at a look-ahead distance. Synthesis conditions of the proposed fuzzy observer are formulated in terms of Linear Matrix Inequalities (LMI) using Lyapunov method. Simulation results show good efficiency of the proposed method to estimate both vehicle dynamics and road geometry.

Road Geometry and Steering Reconstruction for Powered Two Wheeled Vehicles

“…where C is the set of complex numbers, andz denotes the complex conjugate of z. Using the convex sum property of the weighting functions and from (14), sufficient LMI conditions ensuring asymptotic stability in LMI region are obtained as follows :…”

“…Concerning lateral estimation most of cited papers consider restrictive assumptions, regarding riding motorcycle practices and/or a constant longitudinal speed, the road geometry and tire-road contact has often been neglected. To the best of our knowledge, the simultaneous estimation of the lateral dynamics and the road geometry was treated on vehicles and those methods developed for fourwheeled vehicles are not necessarily adequate for motorcycle [14].…”

Considering Variable Road Geometry in Adaptive Vehicle Speed Control

“…Road geometry can reach the best combination by integrated design of the road shapes including horizon, vertical, and cross sections, which can meet not only driver visual and psychological requirements, but also vehicle dynamics and kinematics characteristics, thus reducing the driving work and improving the driving safety, comfort, and economy. Clothoid curves have been used for road geometry design in order to geometrically join a straight road to a curve road, or a straight road to a slope road [3,27,28]. Besides, vertical curves should be used to geometrically join an uphill and a downhill road.…”

Design of Intelligent Vehicle Speed Adaption Based on Variable Road Geometry

“…Due to technical infeasibility and high sensor cost, road geometrical parameters are usually non-measurable in real time. So, many researches focus on estimating road geometry by vehicle sensors available Usually, The road parameters are estimated by means of the sensors, vehicle dynamics and road geometry model, and the estimation results become more accurate (Dahmani et al, 2011;Gutierrez et al, 2011). However, it is obvious that road geometry estimation is based on vehicle sensors, thus, both sensors limitation and delay will prevent vehicle from detecting and using the road geometry (Maeda et al, 2008;Wang et al, 2008).…”