Research On Nonlinear Robust Control Method For Integrated Vehicle Chassis Control System

With the increasing demand of human for the safety and ride comfort of vehicle,the intelligent vehicle,which can realize safety and comfort synthetically,has become one of the main goals of automobile industry among China,Europe,USA and Japan.Active front steering subsystem and direct yaw moment control subsystem are the key actuators to realize lateral dynamic control of intelligent vehicle,and due to their high degree of coupling under the limit driving conditions,it is difficulty to make full use of their properties to improve the comprehensive performance of the full vehicle by integrated control method based on simple combination or superposition.Therefore,the research on integrated control of the active front steering subsystem and direct yaw moment control subsystem under the limit driving conditions has profound theoretical and practical value.Since the vehicle exhibits the characteristics of complex nonlinearity,time variation,strong coupling and uncertainty under the limit driving conditions,it brings great challenges to design and implement the integrated control strategy for the active front steering subsystem and direct yaw moment control subsystem.For the difficulties and challenges,the research work of this paper emphasized on the integrated control method of the active front steering subsystem and direct yaw moment control subsystem,vehicle movement state estimation method and wheel slip tracking control method is surveyed extensively,and the main research results are exhibited as follows.Firstly,a vehicle dynamic model including vehicle dynamics and wheel dynamics and a mathematical model that can accurately reflect the dynamic characteristics of the active hydraulic braking system are established,and then genetic algorithm is applied to identify the unknown parameters of the active hydraulic braking system model.According to the design requirements of integrated vehicle chassis nonlinear robust control law and wheel slip tracking nonlinear robust control law,the vehicle dynamic model is simplified into integrated vehicle chassis control model and wheel slip tracking control model in time scale based on the time scale separation principle.Secondly,the nonlinear robust control method for integrated vehicle chassis control system is investigated.Based on hierarchical thinking,the architecture of integrated vehicle chassis nonlinear robust control law is presented,and it consists of integrated control layer,control allocation layer and execution layer.Consider the integrated vehicle chassis control model with the lumped disturbance,a fast terminal sliding mode control strategy based on the nonlinear disturbance observer,which can effectively improve the dynamic response speed and robustness of the closed-loop system and reduce the chattering of the fast terminal sliding mode control,is proposed to calculate the corrected yaw moment in the integrated control layer,and a hybrid Kalman filter is proposed to estimate the vehicle sideslip angle,which is generally difficult to obtain by direct measurement.Consider the saturation nonlinearity of the tire forces and the constraints of the actuators,the constrained optimization allocation algorithm based on the null space of matrix and the inverse tire model are applied to map the correction yaw moment to the increment of the front wheel steering angle and the desired wheel slips in the control allocation layer.Execution layer is used to track the outputs of the control allocation layer.Subsequently,the effectiveness of the proposed integrated vehicle chassis nonlinear robust control law is verified based on vehicle dynamics simulation software.Further,the wheel slip tracking nonlinear robust control method is concerned in order to make the wheel slip track the desired value in the execution layer.Consider the wheel slip tracking control model with the lumped disturbance,the nonlinear L₂ gain control method is used to restrain the effect of the lumped disturbance on the system performance,and a backstepping sliding mode L2 gain control law for wheel slip tracking is derived based on backstepping sliding mode design framework,that can avoid solving Hamilton-Jacobi-Issacs inequality to attain the objective of the nonlinear L₂ gain control method that the ratio of the L2 norm of the system output to the L2 norm of the lumped disturbance is less than the given threshold value.Subsequently,in order to reduce the conservation of the designed control law,the radial basis function neural network is used to estimate and compensate for the lumped disturbance on-line,and the unknown optimal weight vector of the radial basis function neural network and the unknown parameter characterizing the influence of the tire lateral slip on the tire longitudinal force are updating by adaptive laws,and then an adaptive control law based on radial basis function neural network for wheel slip tracking is proposed.Lastly,the effectivenesses of the proposed nonlinear robust control laws for wheel slip tracking are verified based on vehicle dynamics simulation software.Finally,an integrated vehicle chassis nonlinear robust control prototype is established,and a novel control scheme for brake pressure of wheel cylinder tracking is proposed by combining feed-forward control based on adaptive neuro-fuzzy inference system with PI feedback control to map the desired brake pressures of wheel cylinders to the driving signals of the solenoid valves and direct-current motor of active hydraulic braking system.The hardware-in-the-loop test platform is built based on vehicle dynamic model and real-time hardware system to validate the effectiveness and feasibility of integrated vehicle chassis nonlinear robust control prototype,and it lays the foundation for subsequent development of target electronic control unit.