• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.5
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• pp.138-147
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• 2000

Vehicle suspension systems are parts which effect performances of a vehicle such as ride quality, handing characteristics, straight performance and steering effort etc. Kinematic design is a decision of joints` position for straight performance and steering effort. But, when vehicle is rebounding and bumping, chang of joints` displacement is nonlinear and a surmise of straight performance and steering effort at that joints` position is difficult. So design of suspension systems is done through a inefficient method of tried-and-error depending on designer`s experience. In this paper, kinematic design of suspension systems was done through the optimal design using a genetic algorithm. For this optimal design, the function for quantification of straight performance and steering effort was made, and the kinematic design method of suspension systems having this function as the objective function was suggested.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1205-1210
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• 2001

This paper describes a methodology using neural network to compensate the nonlinear error of deriving speed for electric differential system included in electric vehicle. An electric differential system which drives each of the left and right wheels of the electric vehicle independently. The electric vehicle driven by induction motor has the nonlinear speed error which depends on a steering angle and speed command. When a vehicle drives along a curved road lane, the speed unblance of inner and outer wheels makes vehicles vibration and speed reduction. To compensate for the speed error, we collected the speed data of the inner wheel and outer wheel in various speed and the steering angle data by using an manufactured electric vehicle and the real system. According to the analysis of the acquisited data, we designed the differential speed control system based on a speed error compensator using neural network.

• Journal of Drive and Control
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• v.12 no.3
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• pp.36-43
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• 2015

An autonomous vehicle control algorithm based on Ackerman Geometry is known to be reliable in low tire slip situation. However, vehicles at high speed make lateral errors due to high tire slip. In this paper, considering the tire slip of vehicles, the steering angle is determined based on the Ackerman Geometry and is supplemented tire slip angle by the Stanley steering algorithm. In addition, to prevent the tire slip, the algorithm, which restricts steering if a certain level of slip occurs, is used to reduce the lateral error. While many studies have been extended to include vehicle slip, studies also need to be carried out on the tire slip depending on hardware performance. The control algorithm of autonomous vehicles is compensated considering the sensor noise and the performance of steering actuator. Through the various simulations, it was found that the performance of steering actuator was the key factor affecting the performance of autonomous driving. Also, it was verified that the usefulness of steering algorithm considering the tire slip and performance of steering actuator.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.1
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• pp.19-25
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• 1987

An optimal control procedure is presented for steering of an unmanned cart which has two motored wheels on its left and right side. Steering, running and stopping are enabled by controlling the motor speed independently. An optimal proportional-plus-integral control is employed to eliminate steady state error which is sustained by a simple proportional control for tracking a circular arc path. A simple and readily-implemented suboptimal control is also examined. The suboptimal control gives comparable performance and therefore provides an effective approach for industrial application of the unmanned cart. Effects of design parameters of unmanned cart such as forward velocity, wheel radius and position of sensor are investigated. It is shown that within the practicable values of the parameters the controlled performance improves rapidly with increase of those parameters then the improvement becomes negligible, which suggests base values over which the parameters should be taken.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.10
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• pp.58-66
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• 2008

In the development of intelligent vehicles, path tracking of unmanned vehicle is a basis of autonomous driving and automatic navigation. It is very important to find the exact position of a vehicle for the path tracking, and it is possible to get the position information from GPS. However the information of GPS is not the current position but the past position because a vehicle is moving and GPS has a time delay. In this paper, therefore, the moving distance of a vehicle is estimated using a direction sensor and a velocity sensor to compensate the position error of GPS. In the steering control, optimal fuzzy rules for the path tracking can be found through the simulation of Simulink. Real driving experiments show the fuzzy rules are good for the steering control and the position error of GPS is well compensated by the proposed estimation method.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.5
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• pp.577-585
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• 2015

This paper deals with development of an autopilot system for leisure yacht based on NMEA 2000 network and android platform. The developed system can operate both for manual steering and automatic navigation mode. In automatic steering mode, after manipulation of commands which are NMEA 0183 sentences by android platform, the developed system translates and sends the packets through NMEA 2000 network. Then the controller which is connected to NMEA 2000 network receives the commands and controls the boat's rudder system automatically. The automatic steering mode is achieved by cooperation of two controllers; one for controlling the rudder system, and the other for controlling the vessel's heading. To control the vessel's rudder and heading angle two PID controllers are developed with an adjustable dead-band gain. Also, in order to eliminate the steady-state error occurred by applying dead-band, an integral controller which specifically supervises the system's behavior inside the dead-band area is developed. In this paper, at the first stage, simulations are accomplished using computer in order to examine the feasibility of the proposed based on simulation results. In the next step, the system on a real hydraulic steering model is implemented and at the end the performance examination by implementing it on a real boat and doing test navigation is executed.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.8
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• pp.661-666
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• 2013

A state feedback controller with integration of output error is proposed for way-point tracking of an AUV (Autonomous Underwater Vehicle). For the steering control on the XY plane, the proposed controller uses three state variables (sway velocity, yaw rate, heading angle) and the integral of the steering error, and for the depth control on the XZ plane, it uses four state variables (pitch rate, depth, pitch angle) and the integral of the depth error. From the simulation using Matlab/Simulink, we verify that the performance of the proposed controller is satisfactory within an error range of 1m from the target way-point for arbitrarily chosen sets of consecutive way-points.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1418-1425
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• 2014

In ultrasonic medical imaging, spatial compounding of images is a technique where ultrasonic beam is steered to examine patient tissues in multiple angles. In the conventional ultrasonic diagnostic imaging, the steering of the ultrasonic beam is achieved electronically using the phased array transducer elements. In this paper, a spatial compounding approach is presented where the ultrasonic probe element is rotated mechanically and the beam steering is achieved mechanically. In the spatial compounding, target position is computed using the value of the rotation axis and the transducer array angular position. However, in the process of the rotation mechanism construction and the control system there arises the inevitable uncertainties in these values. These geometric parameter errors result in the target position error, and the consequence is a blurry compounded image. In order to reduce these target position errors, we present a spatial compounding scheme where error correcting transformation matrices are computed and applied to the raw images before spatial compounding to reduce the blurriness in the compounded image. The proposed scheme is illustrated using phantom and live scan images of human knee, and it is shown that the blurriness is effectively reduced.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.861-866
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• 2007

This paper presents development of a vehicle lateral and longitudinal control for autonomous driving control and test results obtained using an electric vehicle. Sliding control theory has been used to develop a vehicle speed and distance control algorithm. The longitudinal control algorithm that maintains safety and comfort of the vehicle consists of a cruise and STOP&GO control depending on traffic conditions. Desired steering angle is determined through the lateral position error and the yaw angle error based on preview optimal control. Motor control inputs have been directly derived from the sliding control law. The performance of the autonomous driving control which is integrated with a lateral and longitudinal control is investigated by computer simulations and driving test using an electric vehicle. Electric vehicle system consists of DC driving motor, an electric power steering system, main controller (Autobox)

• Agricultural and Biosystems Engineering
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• v.6 no.2
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• pp.47-53
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• 2005

AMachine vision is a promising tool for the autonomous guidance of farm machinery. Conventional CCD camera for the machine vision needs a desktop PC to install a frame grabber, however, a web camera is ready to use when plugged in the USB port. A web camera with a notebook PC can replace existing camera system. Autonomous steering control system of this research was intended to be used for combine harvester. If the web camera can recognize cut/uncut edge of crop, which will be the reference for steering control, then the position of the machine can be determined in terms of lateral offset and heading angle. In this research, a white line was used as a cut/uncut edge of crop for steering control. Image processing algorithm including capturing image in the web camera was developed to determine the desired travel path. An experimental vehicle was constructed to evaluate the system performance. Since the vehicle adopted differential drive steering mechanism, it is steered by the difference of rotation speed between left and right wheels. According to the position of vehicle, the steering algorithm was developed as well. Evaluation tests showed that the experimental vehicle could travel within an RMS error of 0.8cm along the desired path at the ground speed of $9\sim41cm/s$. Even when the vehicle started with initial offsets or tilted heading angle, it could move quickly to track the desired path after traveling $1.52\sim3.5m$. For turning section, i.e., the curved path with curvature of 3 m, the vehicle completed its turning securely.