Research On Lateral Robust Fuzzy Control For Intelligent Vehicles

Over recent decades, with the speedy development of social economy and scientific technology, countries around the world have established gridlocked road transport. But there is an indubitable fact that the growth of the number of vehicles has far exceeded the carrying capacity of the existing roads and other traffic facilities. The using of various vehicles brings considerable convenience to human life and work. However, it brings loss to people’s property and threat to lives meanwhile. To solve this problem, governments and researchers all over the world have developed and pay massive attention to Intelligent Transportation System (ITS) to improve road traffic capacity and safety. Automated Highway System (AHS), as a part of ITS, has been extensively concerned. Moreover, lateral control system, which can reduce drivers’fatigue, decrease the ratio of traffic accidents and improve road traffic capacity, is an essential portion of AHS. Nowadays, lateral robust control of intelligent vehicles has become a very consequential research topic. Nonlinearities and uncertainties, such as changes of vehicle parameters and forward speed and external disturbances, affect the stability and safety of highway vehicles enormously and even vitally. The nonlinear system can be represented as a T-S fuzzy system by linear sector approach and be researched by linear system theory. Moreover, the uncertain system can be stabilized by robust control theory. Thereupon, the research of lateral robust fuzzy control to intelligent vehicles has important theory value and practical meaning.The main research works in the thesis are as follows:In chapter1, the problem formulation, practical significance and the research situation home and abroad of this thesis are introduced.In chapter2, the problem of lateral fuzzy H-control to intelligent vehicles is investigated. Firstly, a2-Degree of freedom (DOF) bicycle model is provided, lateral dynamics of a vehicle is represented as a T-S fuzzy model in the basis of the well-known Magic Formula. Secondly, an observer-based controller based on the T-S fuzzy model with a prescribed level of disturbance attenuation to intelligent vehicles is designed by Lyapunov function approach and given in terms of Linear Matrix Inequalities (LMIs). Lastly, the good path tracking performance and passengers’comfortableness of the highway vehicle can be guaranteed by the proposed approach through a Matlab/Simulink-Carsim co-simulation.In chapter3, the problem of the design of lateral robust fuzzy controllers to intelligent vehicles with considerations of membership function deviation is investigated. External disturbances, such as cross wind and variance of road curvature, are explicitly considered in the vehicle modeling. Because tires are prone to enter into saturation region at small tire-road friction coefficient, the nonlinearity is represented by T-S fuzzy model based on the well-known Magic Formula. However, the premise variables of the T-S fuzzy model are immeasurable. In this case, the design of controllers in the basis of the Parallel Distributed Compensation (PDC) is unfeasible. Therefore, the sufficient conditions of existence in terms of LMIs of robust fuzzy controllers to vehicles are derived by non-PDC technique and Lyapunov function approach. Finally, the efficiency of the proposed approach is validated through a Matlab/Simulink-Carsim co-simulation.In chapter4, the main research works of the thesis are concluded, and some research issues in future are prospected.