The Vehicle Steer by Wire Control System by Implementing PID Controller

The latest technology of vehicle steer-by-wire (VSBW) system has promised significant improvement in vehicle safety, dynamics, stability, comfort and maneuverability. Due to complete separation between steering wheel and the front wheels gives the practical problems for steering control especially on directional control and wheel synchronization of vehicle. This paper presents investigations into the development of PID control scheme for directional control and wheel synchronization of a VSBW system. Two PID controllers are used to control the steering wheel angle and front wheel angle. The PID controllers use the front wheel tracking error to generate controlled steering angle. The Ziegler Nichols method is used for tuning the PID parameters. The implementation environment is developed within Matlab/Simulink software for evaluation of performance of the control scheme. Implementation results of the response of the VSBW system with the PID controller are presented in time domains. The performances of control schemes are examined in terms of input tracking capability, wheel synchronization and time response specifications with the absence of disturbances

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

Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains

With the rise of (semi)autonomous vehicles and continuum robotics technology and applications, there has been an increasing interest in controller and haptic interface designs. The presence of nonlinearities in the vehicle dynamics is the main challenge in the selection of control algorithms for real-time regulation and tracking of (semi)autonomous vehicles. Moreover, control of continuum structures with infinite dimensions proves to be difficult due to their complex dynamics plus the soft and flexible nature of the manipulator body. The trajectory tracking and control of automobile and robotic systems requires control algorithms that can effectively deal with the nonlinearities of the system without the need for approximation, modeling uncertainties, and input disturbances. Control strategies based on a linearized model are often inadequate in meeting precise performance requirements. To cope with these challenges, one must consider nonlinear techniques. Nonlinear control systems provide tools and methodologies for enabling the design and realization of (semi)autonomous vehicle and continuum robots with extended specifications based on the operational mission profiles. This dissertation provides an insight into various nonlinear controllers developed for (semi)autonomous vehicles and continuum robots as a guideline for future applications in the automobile and soft robotics field. A comprehensive assessment of the approaches and control strategies, as well as insight into the future areas of research in this field, are presented.First, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. An operator-in-the-loop evaluation that included 30 human test subjects was used to investigate these haptic steering interfaces over a prescribed series of driving maneuvers through real time data logging and post-test questionnaires. A conventional steering wheel with a robust sliding mode controller was used for all the driving events for comparison. Test subjects operated these interfaces for a given track comprised of a double lane-change maneuver and a country road driving event. Subjective and objective results demonstrate that the driver’s experience can be enhanced up to 75.3% with a robotic steering input when compared to the traditional steering wheel during extreme maneuvers such as high-speed driving and sharp turn (e.g., hairpin turn) passing. Second, a cellphone-inspired portable human-machine-interface (HMI) that incorporated the directional control of the vehicle as well as the brake and throttle functionality into a single holistic device will be presented. A nonlinear adaptive control technique and an optimal control approach based on driver intent were also proposed to accompany the mechatronic system for combined longitudinal and lateral vehicle guidance. Assisting the disabled drivers by excluding extensive arm and leg movements ergonomically, the device has been tested in a driving simulator platform. Human test subjects evaluated the mechatronic system with various control configurations through obstacle avoidance and city road driving test, and a conventional set of steering wheel and pedals were also utilized for comparison. Subjective and objective results from the tests demonstrate that the mobile driving interface with the proposed control scheme can enhance the driver’s performance by up to 55.8% when compared to the traditional driving system during aggressive maneuvers. The system’s superior performance during certain vehicle maneuvers and approval received from the participants demonstrated its potential as an alternative driving adaptation for disabled drivers. Third, a novel strategy is designed for trajectory control of a multi-section continuum robot in three-dimensional space to achieve accurate orientation, curvature, and section length tracking. The formulation connects the continuum manipulator dynamic behavior to a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section under the hypothesis of constant curvature. Based on this connection, a computed torque control architecture is developed for the virtual robot, for which inverse kinematics and dynamic equations are constructed and exploited, with appropriate transformations developed for implementation on the continuum robot. The control algorithm is validated in a realistic simulation and implemented on a six degree-of-freedom two-section OctArm continuum manipulator. Both simulation and experimental results show that the proposed method could manage simultaneous extension/contraction, bending, and torsion actions on multi-section continuum robots with decent tracking performance (e.g. steady state arc length and curvature tracking error of 3.3mm and 130mm-1, respectively). Last, semi-autonomous vehicles equipped with assistive control systems may experience degraded lateral behaviors when aggressive driver steering commands compete with high levels of autonomy. This challenge can be mitigated with effective operator intent recognition, which can configure automated systems in context-specific situations where the driver intends to perform a steering maneuver. In this article, an ensemble learning-based driver intent recognition strategy has been developed. A nonlinear model predictive control algorithm has been designed and implemented to generate haptic feedback for lateral vehicle guidance, assisting the drivers in accomplishing their intended action. To validate the framework, operator-in-the-loop testing with 30 human subjects was conducted on a steer-by-wire platform with a virtual reality driving environment. The roadway scenarios included lane change, obstacle avoidance, intersection turns, and highway exit. The automated system with learning-based driver intent recognition was compared to both the automated system with a finite state machine-based driver intent estimator and the automated system without any driver intent prediction for all driving events. Test results demonstrate that semi-autonomous vehicle performance can be enhanced by up to 74.1% with a learning-based intent predictor. The proposed holistic framework that integrates human intelligence, machine learning algorithms, and vehicle control can help solve the driver-system conflict problem leading to safer vehicle operations

Making Transport Safer: V2V-Based Automated Emergency Braking System

An important goal in the field of intelligent transportation systems (ITS) is to provide driving aids aimed at preventing accidents and reducing the number of traffic victims. The commonest traffic accidents in urban areas are due to sudden braking that demands a very fast response on the part of drivers. Attempts to solve this problem have motivated many ITS advances including the detection of the intention of surrounding cars using lasers, radars or cameras. However, this might not be enough to increase safety when there is a danger of collision. Vehicle to vehicle communications are needed to ensure that the other intentions of cars are also available. The article describes the development of a controller to perform an emergency stop via an electro-hydraulic braking system employed on dry asphalt. An original V2V communication scheme based on WiFi cards has been used for broadcasting positioning information to other vehicles. The reliability of the scheme has been theoretically analyzed to estimate its performance when the number of vehicles involved is much higher. This controller has been incorporated into the AUTOPIA program control for automatic cars. The system has been implemented in Citroën C3 Pluriel, and various tests were performed to evaluate its operation

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

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