• Journal of Auto-vehicle Safety Association
• /
• v.15 no.2
• /
• pp.13-20
• /
• 2023

This paper presents a fault tolerant control strategy for Steer-by-Wire (SbW) systems. Among many problems to be solved before commercialization of SbW systems, maintaining reliability and fault tolerance in such systems are the most pressing issues. In most previous studies, dual steering motors are used to achieve actuation redundancy. However, relatively few studies have been conducted to introduce fault tolerant control strategies using rear wheel steering system. In this work, an actuator fault in front wheel steering is compensated by active rear wheel steering. The proposed fault tolerant control algorithm consists of disturbance observer and sliding mode control. The fault tolerant control performance of the proposed approach is validated via computer simulation studies with Carsim vehicle dynamics software and MATLAB/Simulink.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.6
• /
• pp.578-584
• /
• 2015

In this study a moving platform for a mobile robot that can be traveling with a full automatic standing arm was developed. Conventional mobile robots generally may equip 4 wheels or 3 wheels with a caster wheel or independent driven wheels and have good statistic stability. When a mobile robot travels on a sharply perpendicular and narrow crossroad, it may need a special steering scheme such as going forward and backward repeatedly or it is sometimes physically impossible for the robot to go through the crossroad because of the size limit. The upright running mobile robot changes its posture to the upright posture which has a small planar area and is able to go through the crossroad. The upright control which was manually performed step by step before such as sequences of uprighting (returning), checking, and balancing, is now automated.

• Journal of Drive and Control
• /
• v.14 no.2
• /
• pp.9-15
• /
• 2017

The steering systems of all-terrain cranes have been developed with various control strategies for the stability and drivability. To optimally control the input steering angle, an accurate mathematical model that represents the actual crane dynamics is required. The derivation of an accurate mathematical model to optimally control the steering angle, however, is difficult since the steering-control strategy generally varies with the magnitude of the crane's longitudinal velocity, and the postures of the crane's working parts vary while it is being driven. To address this problem, this paper proposes an automatic steering-control algorithm that is based on the MPC (model predictive control) with a disturbance observer for all-terrain cranes. The designed disturbance observer of this study was used to estimate the error between the base steering model and the actual crane. A model predictive controller was used for the computation of the optimal steering angle, along with the use of the base steering model with an estimated uncertainty. Performance evaluations of the designed control algorithms were conducted based on a curved-path scenario in the Matlab/Simulink environment. The performance-evaluation results show a sound reference-path-tracking performance despite the large uncertainties.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.38 no.5
• /
• pp.551-557
• /
• 2014

This paper presents a robust lateral controller for autonomous guidance of a farm tractor in field operations. Although mechanical steering actuators have recently been used for passenger vehicles, the steering actuator of the farm tractor is based on a hydraulic system, resulting in limited bandwidth and a larger time delay. Based on a kinematic tractor model with steering actuator dynamics, a nonlinear control technique called dynamic surface control is applied to design a robust lateral controller that compensates for uncertainty owing to steering actuator and road geometry. Finally, tracking performance and robustness of the proposed controller are validated via commercial tractor simulations, with respect to the time delay of the steering actuator and road geometry (e.g., up and down hills), on a given field with a constant friction coefficient.

• Journal of the Korean Society for Railway
• /
• v.11 no.3
• /
• pp.225-232
• /
• 2008

AWS (all wheel steering) is applied to improve the stability and the turning performance. Most automotive cars are mainly controlled by FWS (front wheel steering) system except some cars which are made to improve their stability by using AWS. Articulated vehicles with a pivoting joint for easy turn are difficult to make a sharp turn because of the long body and long wheelbase. Therefore applying AWS to the articulated vehicles is effective to reduce the turning radius. The AWS control method for the articulated vehicles is currently applied to only Phileas vehicles which were developed by APTS. The paper on the design of a controller to guide an articulated vehicle along the path was published but control algorithm for manual driving has not been reported. In the present paper, steering, characteristics of the Phileas vehicles have been analyzed and then new algorithm has been proposed. To verify the AWS algorithm, Commercial S/W, ADAMS was used for validity of the dynamic model and algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2013.05a
• /
• pp.1115-1116
• /
• 2013

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1996.03a
• /
• pp.67-71
• /
• 1996

The dynamic equation is built by the mathematical modelling. The modelling is composed of various components used for the automatic transmission of tracked vehicles. When the transmission is shifting, the shock occurs in the drivetrain. The transient torques affect the durability and reliability of the vehicle. The factor and design point are analyzed for the transmission.

• Journal of Biosystems Engineering
• /
• v.21 no.3
• /
• pp.283-292
• /
• 1996

Automatic guidance of farm tractors would improve productivity by reducing operator fatigue and increasing machine performance. To control tractors within $\pm$5cm of the desired path, fuzzy and adaptive steering controllers were developed to evaluate their characteristics and performance. Two input variables were position and yaw errors, and a steering command was fed to tractor model as controller output. Trapezoidal membership functions were used in the fuzzy controller, and a minimum-variance adaptive controller was implemented into the 2-DOF discrete-time input-output model. For unit-step and composite paths, a dynamic tractor simulator was used to test the controllers developed. The results showed that both controllers could control the tractor within $\pm$5cm error from the defined path and the position error of tractor by fuzzy controller was the bigger of the two. Through simulations, the output of self-tuning adaptive controller was relatively smooth, but the fuzzy controller was very sensitive by the change of gain and the shape of membership functions. Contrarily, modeling procedure of the fuzzy controller was simple, but the adaptive controller had very complex procedure of design and showed that control performance was affected greatly by the order of its model.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.1
• /
• pp.33-39
• /
• 2014

Automatic driving needs many functions such as the obstacle recognition, the lane recognition, and the lane change, etc. In this paper, we realized a system which automatically drove the three-kinds of vehicle driving course, to introduce and apply the concept of 'color recognition' that expands the scope of 'lane recognition' for vehicle driving. We made the reduced each course compared with RC(Radio Control) car size, and controlled the steering considering the position and the slope of the detection line and the speed. Because the RC car does not have the brake function, we consider the speed and the position of the detection line to stop the RC car.

• Journal of Auto-vehicle Safety Association
• /
• v.11 no.2
• /
• pp.23-28
• /
• 2019

This paper presents an optimal performance of rear wheel steering vehicle for maneuverability. The maneuverability of vehicle is evaluated in terms of yaw rate, body slip angle and driver input. The maneuverability of vehicle can be improved by rear wheel steering system. To obtain optimal performance of rear wheel steering vehicle, the optimal control history is designed. The high dimensional trajectory optimization problem is solved by formulating a quadratic program considering rear wheel steer input. To evaluate handling performance 7 degree-of-freedom vehicle model with actuation sub-models is designed. A step steer test is conducted to evaluate rear wheel steering vehicle. A response time, a TB factor, overshoot, and yaw rate gain are investigated through objective criteria, assessment webs. The handling performance of vehicle is evaluated via computer simulations. It has been shown from simulation studies that optimal controlled rear wheel steering vehicle provides improved performance compared to others.