Vehicle Stability Control Considering the Driver-in-the-Loop

Vehicle Stability;Driver Modeling;Delay;Robust Control;Markov Jump;Linear Parameter Varying Systems

Khosravani, Saeid

University of Waterloo

关键词: Vehicle Stability;    Driver Modeling;    Delay;    Robust Control;    Markov Jump;    Linear Parameter Varying Systems;   

Others  :  https://uwspace.uwaterloo.ca/bitstream/10012/10610/1/khosravani_Saeid.pdf

瑞士|英语

来源: UWSPACE Waterloo Institutional Repository

【 摘 要 】

A driver‐in‐the‐loop modeling framework is essential for a full analysis of vehicle stabilitysystems. In theory, knowing the vehicle’s desired path (driver’s intention), the problem is reducedto a standard control system in which one can use different methods to produce a (sub) optimalsolution. In practice, however, estimation of a driver’s desired path is a challenging – if notimpossible – task. In this thesis, a new formulation of the problem that integrates the driver andthe vehicle model is proposed to improve vehicle performance without using additionalinformation from the future intention of the driver.The driver’s handling technique is modeled as a general function of the road preview informationas well as the dynamic states of the vehicle. In order to cover a variety of driving styles, the time‐varying cumulative driver;;s delay and model uncertainties are included in the formulation. Giventhat for practical implementations, the driver’s future road preview data is not accessible, thisinformation is modeled as bounded uncertainties. Subsequently, a state feedback controller isdesigned to counteract the negative effects of a driver’s lag while makes the system robust tomodeling and process uncertainties.The vehicle’s performance is improved by redesigning the controller to consider a parametervarying model of the driver‐vehicle system. An LPV controller robust to unknown time‐varyingdelay is designed and the disturbance attenuation of the closed loop system is estimated. Anapproach is constructed to identify the time‐varying parameters of the driver model using pastdriving information. The obtained gains are clustered into several modes and the transitionprobability of switching between different driving‐styles (modes) is calculated. Based on thisanalysis, the driver‐vehicle system is modeled as a Markovian jump dynamical system. Moreover,a complementary analysis is performed on the convergence properties of the mode‐dependentcontroller and a tighter estimation for the maximum level of disturbance rejection of the LPVcontroller is obtained. In addition, the effect of a driver’s skills in controlling the vehicle while thetires are saturated is analyzed. A guideline for analysis of the nonlinear system performance withconsideration to the driver’s skills is suggested. Nonlinear controller design techniques areemployed to attenuate the undesirable effects of both model uncertainties and tire saturation.