Research On Fuzzy Modeling And Time-Delayed Steering Control Of Intelligent Vehicle Lateral Dynamic Systems

Steering control can adjust the state of vehicle lateral dynamic systems in real time by active steering inputs.Thus,it contributes greatly to improve vehicle driving stability and has become a research hotspot in field of intelligent vehicle control engineering.However,it is hard to establish an accurate model of the intelligent vehicle lateral dynamic system due to the inherent parameter uncertainties.At the same time,with the wide application of in-vehicle communication network,the communication delay is inevitably encountered in vehicle control systems because of the signal transmission,algorithm operation,control execution and so on.The communication delay brings a new challenge to the state estimation and steering controller design for intelligent vehicles.Motivated by the above concerns,this dissertation employs the fuzzy theory to describe the parameter uncertainties of the system and establishes an accurate model of intelligent vehicle lateral dynamic systems.Furthermore,based on the time-delay system theory,this dissertation uses the linear matrix inequality method to deal with the problems of state estimation and steering controller design for intelligent vehicles.Moreover,the effectiveness of the proposed methods is verified via simulation and experimental tests.1.Based on the two-degree-of-freedom model,the nonlinear characteristics resulted from parameter uncertainties such as tire cornering stiffness,driving speed and vehicle mass are analyzed.Hence,a fuzzy modeling method is proposed to describe intelligent vehicle lateral dynamics,which provides a model basis for system state estimation and steering controller design.At the same time,the influence of communication delay on the system performance is studied.The simulation results show that the communication delay is an important factor to degrade the system performance and even cause system instability.2.Fuzzy modeling and sideslip angle estimation of vehicle lateral dynamic systems with consideration of communication delay.Firstly,a T-S fuzzy fuzzy model is established to describe the lateral dynamic system with varying velocity,nonlinear tire dynamics and vehicle mass uncertainties.Secondly,an adaptive event-triggered mechanism is presented to save the communication resource,and a desired performance index of sideslip angle estimation is given.Thirdly,a new time-delayed filtering method is proposed for the estimation of vehicle sideslip angle.Finally,simulation results verify the advantages of the proposed method in saving the communication resource and estimating the sideslip angle.This is effective to guarantee the feasibility of steering control implementation.3.Focusing on the three elements of communication,road and driver in the cyber-physical space,the problem of time-delayed steering control is studied:Fuzzy modeling and time-delayed steering control of vehicle-road lateral dynamic systems based on event-triggered communication mechanism.Firstly,considering the system nonlinearity and the position relationship between vehicle and road,a T-S fuzzy model is established to approximate the lateral dynamics of the vehicle-road system.Secondly,an adaptive event-triggered mechanism is introduced into the communication scheduling to save the communication resource.Thirdly,aiming at the requirements of vehicle driving stability and path following accuracy,the desired performance index of steering control is given.Moreover,a time-delayed steering control method is proposed based on event-triggered communication mechanism.Finally,hardware-in-the-loop experimental results verify the effectiveness of the proposed method in terms of improving path following accuracy and saving the communication resource.Fuzzy modeling and time-delayed steering control of vehicle-road lateral dynamic systems based on the road curvature frequency domain.Based on the above T-S fuzzy model of the vehicle-road system,a finite frequency control performance index is established based on the road curvature frequency domain.Then,a time-delayed steering control method in the form of state feedback is proposed.Furthermore,to eliminate the dependence on immeasurable variables,a time-delayed steering control method in the form of output feedback is proposed through matrix separation.Finally,hardware-in-the-loop experimental results show that the proposed methods can further improve the vehicle dynamic stability and path following performance.Fuzzy modeling and time-delayed steering control of driver-vehicle-road lateral dynamic systems based on human-machine shared control.Firstly,a T-S fuzzy model is established to describe global driver-vehicle-road systems with driving behavioral uncertainties and dynamic nonlinearities.Secondly,based on the above fuzzy model,an observed-state-feedback-based time-delayed steering control method is proposed.At the same time,a sampled-outputfeedback-based time-delayed steering control method is proposed.Finally,co-simulation results and driver-in-the-loop experimental results verify the effectiveness of the proposed methods in the improvement of driving comfort and vehicle dynamic performances,respectively.