Robust composite nonlinear feedback for nonlinear Steer-by-Wire vehicle’s Yaw control

Yaw control is a part of an Active Front Steering (AFS) system, which is used to improve vehicle manoeuvrability. Previously, it has been reported that the yaw rate tracking performance of a linear Steer-by-Wire (SBW) vehicle equipped with a Composite Nonlinear Feedback (CNF) controller and a Disturbance Observer (DOB) is robust with respect to side wind disturbance effects. This paper presents further investigation regarding the robustness of the combination between a CNF and a DOB in a nonlinear environment through a developed 7-DOF nonlinear SBW vehicle. Moreover, in contrast to previous studies, this paper also contributes in presenting the validation works of the proposed control system in a real-time situation using a Hardware-in-Loop (HIL) platform. Simulation and validation results show that the CNF and DOB managed to reduce the influence of the side wind disturbance in nonlinearities

A Review of Active Yaw Control System for Vehicle Handling and Stability Enhancement

Yaw stability control systemplays a significant role in vehicle lateral dynamics in order to improve the vehicle handling and stability performances. However, not many researches have been focused on the transient performances improvement of vehicle yaw rate and sideslip tracking control. This paper reviews the vital elements for control system design of an active yaw stability control system; the vehicle dynamic models, control objectives, active chassis control, and control strategies with the focus on identifying suitable criteria for improved transient performances. Each element is discussed and compared in terms of their underlying theory, strengths, weaknesses, and applicability. Based on this, we conclude that the sliding mode control with nonlinear sliding surface based on composite nonlinear feedback is a potential control strategy for improving the transient performances of yaw rate and sideslip tracking control

Enhanced active front steering control using sliding mode control under varying road surface condition

In vehicle lateral dynamic control, the handling quality or steering ability of the vehicle is determined by the yaw rate response performances. The uncertainty of tire cornering stiffness due to varying tire-road adhesion coefficient, u caused by road surfaces perturbation during cornering manoeuvre may influence the transient performances of yaw rate response. Therefore, in this research, the enhanced control law of robust yaw rate tracking controller using the Sliding Mode Control (SMC) algorithm is proposed for active front steering (AFS) control strategy to improve the yaw rate response as desired. The vehicle lateral dynamics behaviors are described using the linear and nonlinear vehicle models. The linear 2 degree-of-freedom (DOF) single track model is used for controller design while the nonlinear 7 DOF two-track model is used for simulation and controller evaluations. The sliding surface of SMC is design based on yaw rate tracking error information. The control law equation is enhanced by integrating the uncertainty of cornering stiffness at the front wheels and to ensure the controller stability, the Lyapunov stability theory is applied. The transient performances and performance indices of AFS control responses are evaluated using the step steer and single lane change cornering manoeuvres test for varying values of u at dry, wet and snow or icy road surfaces. The simulations results demonstrated that the proposed enhanced control law using SMC is able to track the reference yaw rate with similar transient response performances. The proposed enhanced control law also provided low performance indices of ITAE and IAE compared to the conventional control law using SMC and robust CNF control for lower value of u at wet and snow or icy road surface. In terms of percentage of differential performance indices, the proposed control law has a better tracking ability of up to 58.45% compared to two other control laws. Therefore, this research concluded that the proposed enhanced control law using SMC has overcome the cornering stiffness uncertainty in AFS control strategy for different road surfaces during cornering manoeuvre and this enhancement is expected as a knowledge contribution to vehicle lateral dynamic study

Improving transient performances of vehicle yaw rate response using composite nonlinear feedback

This paper studies and applied the composite nonlinear feedback (CNF) control technique for improving the transient performances of vehicle yaw rate response. In the active front steering control design and analysis, the linear bicycle model is used for controller design while the 7DOF nonlinear vehicle model is used as vehicle plant for simulation and controller evaluations. The vehicle handling test of the J-turn and single lane change maneuvers are implemented in computer simulations in order to evaluate the designed yaw rate tracking controller. The simulation results show that the CNF technique could improve the transient performances of yaw rate response and enhance the vehicle maneuverability

HAPTICS IN ROBOTICS AND AUTOMOTIVE SYSTEMS

Haptics is the science of applying touch (tactile) sensation and control to interaction with computer applications. The devices used to interact with computer applications are known as haptic interfaces. These devices sense some form of human movement, be it finger, head, hand or body movement and receive feedback from computer applications in form of felt sensations to the limbs or other parts of the human body. Examples of haptic interfaces range from force feedback joysticks/controllers in video game consoles to tele-operative surgery. This thesis deals with haptic interfaces involving hand movements. The first experiment involves using the end effector of a robotic manipulator as an interactive device to aid patients with deficits in the upper extremities in passive resistance therapy using novel path planning. The second experiment involves the application of haptic technology to the human-vehicle interface in a steer-by-wire transportation system using adaptive control

The virtual force feedback for torque estimation and control in a vechicle Steer by Wire (SBW) system

This study presents the method to generates and control a force feedback with torque control for a driver steering feel in a vehicle steer by wire (SBW) system. The control algorithm of force feedback was developed by simulation and validated through experimental to investigated the steering and control performance. This is done by constructed a steering wheel rig hardware in the loop (HIL) and interfaced to Matlab XPC target software. Two method are proposed to generate and control a force feedback whereby the current measurement is a main element used to estimates the steering torque . For the first control algorithm, the torque at the front axle system and self aligning are used to generate a force feedback and the PID controller with fuzzy system (PID+Fuzzy) are used to control a feedback torque. Meanwhile, the reference model was used to improves the centering steering wheel position. For a second control algorithm, the torque map and torque of steering wheel and front axle system are used to generate the force feedback. Meanwhile, the LQR control with gain scheduling (LQR+GS) are used to control the torque. Furthermore, the compensation torque is used to improves the steering feel and to stabilize the system by varying a compensation gains. The results demonstrate shown, that the torque control using a LQR+GS method is improves against a torque map and 90% similar to Electric Power Steering (EPS) system. This is because there are multiple gains varying that able to improve a steering control performance. On the others hand, the hyperbolic tangent and linear equation proposed improves a vehicle maneuverability at low and high speed

Newly Developed Nonlinear Vehicle Model for an Active Anti-roll Bar System

This paper presents the development of a newly developed nonlinear vehicle model is used in the validation process of the vehicle model. The parameters chosen in a newly developed vehicle model is developed based on CARSIM vehicle model by using non-dominated sorting genetic algorithm version II (NSGA-II) optimization method. The ride comfort and handling performances have been one of the main objective to fulfil the expectation of customers in the vehicle development. Full nonlinear vehicle model which consists of ride, handling and Magic tyre subsystems has been derived and developed in MATLAB/Simulink. Then, optimum values of the full nonlinear vehicle parameters are investigated by using NSGA-II. The two objective functions are established based on RMS error between simulation and benchmark system. A stiffer suspension provides good stability and handling during manoeuvres while softer suspension gives better ride quality. The final results indicated that the newly developed nonlinear vehicle model is behaving accurately with input ride and manoeuvre. The outputs trend are successfully replicated

State and parameter estimator design for control of vehicle suspension system

Modern vehicle stability and navigational systems are mostly designed using inaccurate bicycle models to approximate the full-car models. This results in incomplete models with various unknown parameters and states being neglected in the controller and navigation system design processes. Earlier estimation algorithms using the bicycle models are simpler but have many undefined parameters and states that are crucial for proper stability control. For existing vehicle navigation systems, direct line of sight for satellite access is required but is limited in modern cities with many high-rise buildings and therefore, an inertial navigation system utilizing accurate estimation of these parameters is needed. The aim of this research is to estimate the parameters and states of the vehicle more accurately using a multivariable and complex full-car model. This will enhance the stability of the vehicle and can provide a more consistent navigation. The proposed method uses the kinematics estimation model formulated using special orthogonal SO3 group to design estimators for vehicles velocity, attitude and suspension states. These estimators are used to modify the existing antilock braking system (ABS) scheme by incorporating the dynamic velocity estimation to reduce the stopping distance. Meanwhile the semi-active suspension system includes suspension velocity and displacement states to reduce the suspension displacements and velocities. They are also used in the direct yaw control (DYC) scheme to include mass and attitude changes to reduce the lateral velocity and slips. Meanwhile in the navigation system, the 3-dimensional attitude effects can improve the position accuracy. With these approaches, the stopping distance in the ABS has been reduced by one meter and the vehicle states required for inertial navigation are more accurately estimated. The results for high speed lane change test indicate that the vehicle is 34% more stable and 16% better ride comfort on rough terrains due to the proposed DYC and the active suspension system control. The methods proposed can be utilized in future autonomous car design. This research is therefore an important contribution in shaping the future of vehicle driving, comfort and stability