• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.33-39
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• 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 Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1137-1147
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• 2004

In this paper, we proposed two types of adaptive control mechanism which is named HIA(Humoral Immune Algorithm) PID and CMIA(Cell-Mediated Immune Algorithm) controller based on biological immune system under engineering point of view. The HIA PID which has real time control scheme is focused on the humoral immunity and the latter which has the self-tuning mechanism is focused on the T-cell regulated immune response. To verify the performance of the proposed controller, some experiments for the control of AGV which is used for the port automation to carry container without human are performed. The experimental results for the control of steering and speed of an AGV system illustrate the effectiveness of the proposed control scheme. Moreover, in that results, proposed controllers have better performance than other conventional PID controller and intelligent control method which is the NN(neural network) PID controller.

• Journal of Mechanical Science and Technology
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• v.16 no.3
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• pp.338-343
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• 2002

In the autonomous vehicle, the reference lane is continually detected by machine vision system. And then the vehicle is steered to follow the reference yaw rates which are generated by the deviations of lateral distance and the yaw angle between a vehicle and the reference lane. To cope with the steering delay and the side-slip of vehicle, PI controller is introduced by yaw rate feedback and tuned from the simulation where the vehicle is modeled as 2 DOF and 79 DOF and verified by the results of an actual vehicle test. The lateral control algorithm by yaw rate feedback has good performances of lane tracking and passenger comfort.

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.445-453
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• 2007

This paper presents a robust controller design approach for improving vehicle dynamic roll motion performance and guaranteeing the closed-loop system stability in spite of vehicle parameter variations resulting from aging elements, loading patterns, and driving conditions, etc. The designed controller is linear parameter-varying (LPV) in terms of the time-varying parameters; its control objective is to minimise the $H_{\infty}$ performance from the steering input to the roll angle while satisfying the closed-loop pole placement constraint such that the optimal dynamic roll motion performance is achieved and robust stability is guaranteed. The sufficient conditions for designing such a controller are given as a finite number of linear matrix inequalities (LMIs). Numerical simulation using the three-degree-of-freedom (3-DOF) yaw-roll vehicle model is presented. It shows that the designed controller can effectively improve the vehicle dynamic roll angle response during J-turn or fishhook maneuver when the vehicle's forward velocity and the roll stiffness are varied significantly.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.671-672
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• 2008

Hybrid intelligent technique is used in ship steering control. It can make full use of the advantage of all kinds of intelligent algorithms. This provides an efficient way for this paper. An RBF neural network and GA optimization are employed in a fuzzy neural controller to deal with the nonlinearity, time varying and uncertain factors. Utilizing the designed network to substitute the conventional fuzzy inference, the rule base and membership functions can be auto-adjusted by GA optimization. The parameters of neural network can be decreased by using union-rule configuration in the hidden layer of the network. The ship control quality is effectively improved in case of appending additional sea state disturbance. The performance of controller is evaluated by the system simulation using Matlab.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.604-609
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• 2004

Recently, various studies had been made for automatic control system of small ships, in order to improve maneuvering and to reduce labor and working on board. To achieve efficient operation of small ships, it had been accomplished to rapid development of automatic technique, but the ship operation had been more complicated because of the need to handle various gauges and instruments. To solve these problems, there are examples to be applied to the speech information processing technologies which is one of the human interface methods in the system operation of ship, but the implementation of definite system is still incomplete. Therefore, the purpose of this paper is to implement the control system for ship steering using the voice recognition module.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.6
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• pp.1-9
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• 2008

The current test methods are insufficient to evaluate and ensure the safety and reliability of vehicle system for all possible dynamic situation including the worst case such as rollover, spin-out and so on. Although the known NHTSA J-turn and Fish-hook steering maneuvers are applied for the vehicle performance assessment, they aren't enough to estimate other possible worst case scenarios. Therefore, it is crucial for us to verify the various worst cases including the existing severe steering maneuvers. This paper includes the procedure to search for other useful worst case based upon the existing worst case scenarios mentioned above and its application in simulation basis. The only human steering angle is selected as a design parameter here and optimized to maximize the index function to be expressed in terms of either roll angle or yaw rate. The obtained scenarios were enough to generate the worst case to meet NHTSA worst case definition (ex.2-inch wheel lift). Additionally, as an application, the worst case steering maneuver is acquired for the vehicle to operate with a simple ESP system. It has been concluded that the new procedure in this paper is adequate to create other feasible worst case scenarios for a vehicle system both with an intelligent safety control system and without it.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.4
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• pp.313-323
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• 2017

As vehicles become more intelligent this is focused on ways to enhance safety and convenience for both drivers and passengers. In particular, x-by-wire systems that replace rigid mechanical components with dynamically configurable electronic elements are being developed to expand intelligent functions, such as adaptive cruise control or lane departure warning system. Because the malfunction of safety-related modules controlling critical functions, such as brakes, throttle, and steering in x-by-wire systems, can cause injury or death, safety and reliability are the most critical issue for automotive vendors and parts manufacturers. In an effort to develop better and effective brake-by-wire system, this paper presents EMB system by using the low speed electric vehicle, which is not required large braking force, with motor controller. In addition, we design performance evaluation system of EMB with 1/4 low speed electric vehicle model and suggested EMB is evaluated through the performance evaluation system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.287-291
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• 2003

현대의 선박운항에 있어서 선내 노동의 경감과 운항의 안정성 및 경제성 확보를 위하여 선박 자동화 및 원격 조종화가 이루어지고 있다. 또한, 선박조종 및 작업제어를 위하여 컴퓨터를 이용한 통합제어 시스템에 관한 연구도 활발하게 진행되고 있다. 그러나 소형선박 빛 어선과 같은 환경에서의 지능형 시스템에 관한 연구는 많이 부족한 실정이다. 인공지능기법을 이용하여 보다 인간 친화적인 시스템을 구현하고, 음성인식기술을 이용하여 원격으로 선박 조타기를 제어하여 조업자의 부담경감 및 인원절감의 효과를 가져올 수 있는 선박 조종시스템의 개발이 절실하다. 본 논문에서는 PC를 기반으로 하여 원격으로 모형 선박의 조타기를 제어하는 시스템을 구축하였다. 구체적인 연구 방법으로는, 음성인식기술과 지능형 학습 기법을 바탕으로 음성지시기반학습 시스템을 구축하고, 퍼지 조타수 조작모델을 구현하여 PC 기반 원격 제어시스템을 구현하였다. 또한, 구축된 원격 조타제어시스템을 축소된 선박모형(Miniature Ship) 시스템에 적용하여 그 효용성을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.196-196
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, teaming itself, and the adequacy of the design controller. The performance of the controller can be verified through simulation. The real autonomous electric vehicle using neural network controller verified good results.