The aim of this paper is to develop an active steering assistance system to avoid the rollover of heavy vehicles (HV). The proposed approach is applied on a single body model of HV presented in this paper. An estimator based on the high-order sliding mode observer is developed to estimate the vehicle dynamics, such as lateral acceleration limit and center height of gravity. Lateral position and lateral speed are controlled using a twisting algorithm to ensure the stability of the vehicle and avoid accidents. At the same time, the identification of unsprung masses and suspension stiffness parameters of the model have been computed to increase the robustness of the method. Some simulation and experimental results are given to show the quality of the proposed concept
Vehicles are complex mechanical systems with strong nonlinear characteristics and which can present some uncertainties due to their dynamic parameters such as masses, inertias, suspension springs, tires side slip coefficients, etc. A vehicle is composed of many parts, namely the unsprung mass, the sprung mass, the suspension which makes the link between these two masses and therefore ensures passenger comfort, and also the pneumatic which absorbs the energy coming from the road and ensures contact between the vehicle and the road. In addition to its complexity and the presence of many nonlinearities and uncertainties, the presence of some external perturbations, such as the wind and the road inputs with its own characteristics (radius of curvature, longitudinal and lateral slop, road profile and skid resistance) can cause risks not only to the vehicle but also to passengers and other road users. Many methods have been developed in order to understand the behavior of a vehicle, control it and assist the driver in order to avoid possible lane departures, rollover or jackknifing risks, to ensure a better passenger comfort by means of a suspension control and/or to estimate a safety speed and trajectory. The present book is an attempt to show how the sliding mode based observation, uncertainties identification and parameter estimation may be applied in the control of vehicle dynamics as well as for parameter and perturbations estimation
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