Analysis And Control Of Vehicle Active Front Steering Systems

Vehicle steering systems are important guarantees for vehicle driving safety,which can control the vehicle to move forward or backward,and their performance affects the maneuverability and stability of the vehicle driving.According to the driving state of the vehicle in real time,the active front steering systems not only adjust the transmission ratio appropriately to realize the normal steering operation,but also improve the steering sensitivity of running at low speed and the stability of steering at high speed.Therefore,the active front steering systems are hot research topics in the field of vehicle active safety currently,which has important research value and social significance.In the process of system modeling,the uncertainties of vehicle mass and moment of inertia should be considered.Takagi-Sugeno(T-S)fuzzy model is an effective method to represent the complex nonlinear systems.Based on the T-S fuzzy model,the systems can be described as the weighted sum of some simple linear subsystems.However,in the uncertain systems,the membership function of type-1 T-S fuzzy model is accurate,which may affect the control effect of the systems.Therefore,the active front steering systems are constructed as an interval type-2 fuzzy system,and the upper and lower membership functions are used to capture the uncertain parameters of the system.In addition,in the complex working environment,the active front steering systems may inevitably produce many problems,such as the unmeasurable states 、 time-delay 、 data dropout、 actuator failure、actuator saturation、sensor failure and so on.Based on the above problems,we have carried out research work and achieved the following research results:1.For the uncertain active front steering systems,the systems are constructed as a type-1 T-S fuzzy system.Because the states of the system are unmeasurable,a state observer is designed to estimate the states of the system.Based on Lyapunov stability theory and linear matrix inequality method,sufficient conditions that the closed-loop system is asymptotically stable are obtained,and the controller gain also is obtained.Single-lane change simulation results based on vehicle dynamics model verify the effectiveness of the fuzzy control method.2.The fuzzy fault-tolerant control problem for the uncertain vehicle active front steering systems is studied.By adopting type-1 T-S fuzzy method,the steering time-delay systems are established as a T-S fuzzy system.When the system has actuator failure,a failure model is introduced to describe this phenomenon.Based on Lyapunov stability theory,the conditions for proving that the closed-loop system is asymptotically stable are obtained.By decoupling,the gain of state-feedback controller is obtained.Single-lane change simulation results based on vehicle dynamics model further verify the effectiveness of the fuzzy control method.3.For the uncertain vehicle active steering systems,by employing interval type-2 fuzzy method,the systems are constructed as an interval type-2 fuzzy system and the upper and lower membership functions are used to describe the uncertainty of the system.Meanwhile,the saturated nonlinear problem is solved by employing norm-bounded method.In addition,a general fault model is introduced to describe the sensor failures.When the sensor failure and actuator saturation occur,an interval type-2 fuzzy controller is designed.Based on Lyapunov stability theory,sufficient conditions for proving that the system is quadratically stable are obtained.Finally,simulation results based on vehicle dynamics model further verify the effectiveness of the interval type-2 fuzzy control strategy.