A Novel Integrated Stability Control Based on Differential Braking and Active Steering for Four-axle Trucks

Di erential braking and active steering have already been integrated to overcome their shortcomings. However, existing research mainly focuses on two-axle vehicles and controllers are mostly designed to use one control method to improve the other. Moreover, many experiments are needed to improve the robustness; therefore, these control methods are underutilized. This paper proposes an integrated control system specially designed for multi-axle vehicles, in which the desired lateral force and yaw moment of vehicles are determined by the sliding mode control algorithm. The output of the sliding mode control is distributed to the suitable wheels based on the abilities and potentials of the two control methods. Moreover, in this method, fewer experiments are needed, and the robustness and simultaneity are both guaranteed. To simplify the optimization system and to improve the computation speed, seven simple optimization subsystems are designed for the determination of control outputs on each wheel. The simulation results show that the proposed controller obviously enhances the stability of multi-axle trucks. The system improves 68% of the safe velocity, and its performance is much better than both di erential braking and active steering. This research proposes an integrated control system that can simultaneously invoke di erential braking and active steering of multi-axle vehicles to fully utilize the abilities and potentials of the two control methods.

Vehicle Active Steering Control Research Based on Two-DOF Robust Internal Model Control

Because of vehicle＇s external disturbances and model uncertainties,robust control algorithms have obtained popularity in vehicle stability control.The robust control usually gives up performance in order to guarantee the robustness of the control algorithm,therefore an improved robust internal model control（IMC） algorithm blending model tracking and internal model control is put forward for active steering system in order to reach high performance of yaw rate tracking with certain robustness.The proposed algorithm inherits the good model tracking ability of the IMC control and guarantees robustness to model uncertainties.In order to separate the design process of model tracking from the robustness design process,the improved 2 degree of freedom（DOF） robust internal model controller structure is given from the standard Youla parameterization.Simulations of double lane change maneuver and those of crosswind disturbances are conducted for evaluating the robust control algorithm,on the basis of a nonlinear vehicle simulation model with a magic tyre model.Results show that the established 2-DOF robust IMC method has better model tracking ability and a guaranteed level of robustness and robust performance,which can enhance the vehicle stability and handling,regardless of variations of the vehicle model parameters and the external crosswind interferences.Contradiction between performance and robustness of active steering control algorithm is solved and higher control performance with certain robustness to model uncertainties is obtained.

Control of Vehicle Active Front Steering Based on Active Disturbance Rejection Feedback Controller

A control method of active front steering(AFS)based on active disturbance rejection technique was proposed for solving the model nonlinearity and parameter decoupling control in the traditional control methods.The AFS controller consists of the proportional and derivative(PD)feed-forward controller and the active disturbance rejection feedback controller.To improve the steering response characteristics of a vehicle,a PD controller is designed to realize variable steering gear ratio,and to enhance the safety of vehicle when steering.An active disturbance rejection controller(ADRC)is designed to follow the expected yaw rate of the vehicle.According to the input and output of system,extended state observer(ESO)of ADRC can dynamically estimate internal and external disturbance of the system,thus easily realizing the model nonlinear and parameter decoupling control.The AFS controller is simulated and validated in Matlab and CarSim.The simulating results of double lane change(DLC)test and pylon course slalom(PCS)test show that the ADRC can well control the vehicle model to complete the road simulation test of DLC and PCS with small path tracking error.The simulating results of angle step test of steering wheel show that the vehicle under the control of ADRC demonstrates good lateral response characteristic.The controller regulates a wide range of parameters.The model has less precision requirements with good robustness.

ACTIVE FRONT STEERING DURING BRAKING PROCESS

An active front steering （AFS） intervention control during braking for vehicle stability is presented. Based on the investigation of AFS mechanism, a simplified model of steering system is established and integrated with vehicle model. Then the AFS control on vehicle handling dynamics during braking is designed. Due to the difficulties associated with the sideslip angle measurement of vehicle, a state observer is designed to provide real time estimation. Thereafter, the controller with the feedback of both sideslip and yaw angle is implemented. To evaluate the system control, the proposed AFS controlled vehicle has been tested in the Hardware-in-the-loop-simulation （HILS） system and compared with that of conventional vehicle. Results show that AFS can improve vehicle lateral stability effectively without reducing the braking performance.

Generalized Internal Model Robust Control for Active Front Steering Intervention

Because of the tire nonlinearity and vehicle＇s parameters＇uncertainties,robust control methods based on the worst cases,such as H_∞,μsynthesis,have been widely used in active front steering control,however,in order to guarantee the stability of active front steering system（AFS）controller,the robust control is at the cost of performance so that the robust controller is a little conservative and has low performance for AFS control.In this paper,a generalized internal model robust control（GIMC）that can overcome the contradiction between performance and stability is used in the AFS control.In GIMC,the Youla parameterization is used in an improved way.And GIMC controller includes two sections：a high performance controller designed for the nominal vehicle model and a robust controller compensating the vehicle parameters＇uncertainties and some external disturbances.Simulations of double lane change（DLC）maneuver and that of braking on split-μroad are conducted to compare the performance and stability of the GIMC control,the nominal performance PID controller and the H_∞controller.Simulation results show that the high nominal performance PID controller will be unstable under some extreme situations because of large vehicle＇s parameters variations,H_∞controller is conservative so that the performance is a little low,and only the GIMC controller overcomes the contradiction between performance and robustness,which can both ensure the stability of the AFS controller and guarantee the high performance of the AFS controller.Therefore,the GIMC method proposed for AFS can overcome some disadvantages of control methods used by current AFS system,that is,can solve the instability of PID or LQP control methods and the low performance of the standard H_∞controller.

Improving rail vehicle dynamic performance with active suspension

Today,it is difficult to further improve the dynamic performance of rail vehicles with conventional passive suspension.Also,simplified vehicle respectively running gear layouts that significantly could reduce vehicle weights are difficult to realize with modern requirements on passenger vibration comfort and wheel and rail wear.Active suspension is a powerful technology that can improve the vehicle dynamic performance and make simplified vehicle concepts possible.The KTH Railway group has,together with external partners,investigated active suspensions both numerically and experimentally for 15 years.The paper provides a summary of the activities and the most important findings.One major project carried out in close collaboration with the vehicle manufacturer Bombardier and the Swedish Transport Administration was the Green Train project,where a 2-car EMU test bench was used to demonstrate different active technologies.In ongoing projects,a concept of single axle-single suspension running gear is developed with active suspension both for comfort improvement and reduced wheel wear in curves.The results from on-track tests in the Green Train project were so good that the technology is now implemented in commercial trains and the simulation results for the single-axle running gear are very promising.

Multi-constrained model predictive control for autonomous ground vehicle trajectory tracking

A multi-constrained model predictive control （ MPC ） algorithm for trajectory tracking of an autonomous ground vehicle is proposed and tested in this paper. First, to simplify the computa- tion, an active steering linear error model is applied in the MPC controller. Then, a control incre- ment constraint and a relaxing factor are taken into account in the objective function to ensure the smoothness of the trajectory, using a softening constraints technique. In addition, the controller can obtain optimal control sequences which satisfy both the actual kinematic constraints and the actuator constraints. The circular trajectory tracking performance of the proposed method is compared with that of another MPC controller. To verify the trajectory tracking capabilities of the designed control- ler at different desired speed, the simulation experiments are carried out at the speed of 3m/s, 5m/ s and 10m/s. The results demonstrate the MPC controller has a good speed adaptability.

Study of active beam steering system with a simple method

We develope a simple method to stabilize the beam during propagation. Combination of the self-developed control module and the large diameter mirrors reconstruct the beam stabilization system, and some important procedures are presented, such as calibration arid average filter. The results show that the horizontal pointing and vertical pointing are stabilized to within 8.43 and 7.59 μrad, and the beam horizontal position and vertical position are stabilized to within 2.16 and 2.11 μm respectively. The regulating time is within 84 ms. Thus the method presented is effective for the current stabilization system applied in lithography tools.