• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.1850-1851
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• 2006

The sliding mode control is acceptable for Autonomous Underwater Vehicle(AUV), since the dynamics of AUV are highly nonlinear and have several parameter uncertainty such as the added mass terms, the hydrodynamic coefficients. The sliding mode control can deal well with nonlinearity of the system and offers a robustness to controller with parameter uncertainty. Since sliding mode control has the defect of chattering problem, only in ideal case the actuator can respond by control law. Therefore we propose the sliding mode control with non-chattering. And computer simulations illustrate the performance of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.173.4-173
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• 2001

This paper presents a stable nonlinear adaptive control for AUV(Autonomous Underwater Vehicle) by using neural network. AUV's dynamics are highly nonlinear, and their hydrodynamic coefficients vary with different operational conditions. In this paper, the nonlinear uncertainties of the AUV's dynamics are approximated by using LPNN(Linearly parameterized Neural Network). The presented controller is consist of three parallel terms; linear feedback control, sliding mode control, and adaptive control(LPNN). Lyapunov theory is used to guarantee the stability of tracking errors and neural network´s weights errors. Numerical simulations for nonlinear control of the AUV show the effectiveness of the proposed techniques.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.51-55
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• 1997

This study is devote to developing navigation filter for detecting sensor failure in multi-sensor navigation system. In multi-sensor navigation system, Kalman filter is generally used to fuse data of each sensors. Sensor failure is fatal in case that the sensor is used as external measurement of Kalman filter therefore detection and recovery of sensor failure is one the important feature of navigation filter. Generally each sensors have its specific feature in measuring navigational information. Fuzzy theory is proposed to detect external sensor failure and provide valid external measurement to Kalman filter avoiding filter divergence and instability. This idea is applied to Autonomous Underwater Vehicle(AUV) which has two navigation sensor i. e self contained inertial sensor and acoustic external sensor. 2 dimensional simulation result shows acceptable failure detection and recovery

• Advances in Computational Design
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• 제5권3호
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• pp.233-260
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• 2020

The main purpose to introduce model based controller in proposed control technique is to provide better and fast learning of the floating dynamics by means of fuzzy logic controller and also cancelling effect of nonlinear terms of the system. An iterative adaptive dynamic programming algorithm is proposed to deal with the optimal trajectory-tracking control problems for autonomous underwater vehicle (AUV). The optimal tracking control problem is converted into an optimal regulation problem by system transformation. Then the optimal regulation problem is solved by the policy iteration adaptive dynamic programming algorithm. Finally, simulation example is given to show the performance of the iterative adaptive dynamic programming algorithm.

• International Journal of Naval Architecture and Ocean Engineering
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• 제10권4호
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• pp.499-507
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• 2018

Autonomous Underwater Vehicle (AUV), which are becoming more and more important in ocean exploitation tasks, needs energy conservation urgently when sailing the complex mission path in long time cruise. As hull lines optimization design becomes the key factor, which closely related with resistance, in AUV preliminary design stage, uncertainty parameters need to be considered seriously. In this research, Myring axial symmetry revolution body with parameterized expression is assumed as AUV hull lines, and its travelling resistance is obtained via modified DATCOM formula. The problems of AUV hull lines design for the minimum travelling resistance with uncertain parameters are studied. Based on reliability-based optimization design technology, Design For Six Sigma (DFSS) for high quality level is conducted, and is proved more reliability for the actual environment disturbance.

• Journal of Mechanical Science and Technology
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• 제20권8호
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• pp.1159-1168
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• 2006

In this paper, a new revolute mobile robot arm with five degree of freedom (d.o.f) was developed for autonomous moving robots. As a control system for the robot arm, a distributed control system composed of the main controller and five motor controllers for arm joints was developed. The main controller and the motor controllers w ε re developed using the ARM microprocessor and the TMS320c2407 microprocessor, respectively. A new trajectory tracking algorithm for the motor controllers was devised employing pre-generated off-line trajectory data. Also, a 3-D simulator based on the openGL software to simulate the motion of the robot arm was developed. To validate the performance of the robot system, experiments to track a specified trajectory were performed.

• 전기학회논문지
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• 제57권7호
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• pp.1241-1246
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• 2008

The dynamics of mobile robot is nonlinear. To cope with this nonlinearity, many advanced control schemes have been proposed recently. Generally, the advanced control schemes are complicated and not good for the practical real-time control when they are implemented as control programs. So, in this paper, a relatively simple PI controller is proposed and applied to the position control of mobile robot with the adoption of reference trajectory calculation method used for the AUV(Autonomous Underwater Vehicle) control. The proposed PI controller is programmed using LabVIEW which is popular for its graphical programming characteristics. The simulation and experimental results show the feasibility and effectiveness of the proposed PI controller.

• 반도체디스플레이기술학회지
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• 제19권3호
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• pp.124-129
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• 2020

Autonomous underwater vehicle makes attracts to many researchers. This paper proposes a convolutional neural network (CNN) based fish detection method. Since there are not enough data sets in the process of training, overfitting problem can be occurred in deep learning. To solve the problem, we apply the dropout algorithm to simplify the model. Experimental result showed that the implemented method is promising, and the effectiveness of identification by dropout approach is highly enhanced.

• 제어로봇시스템학회지
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• 제17권2호
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• pp.36-46
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• 2011

자율무인잠수정(Autonomous Underwater Vehicle, AUV)은 미국을 중심으로 1980년대부터 다양한 수중관련 기술의 발전과, 민군의 사용분야가 증가되면서 급속한 발전의 진전을 보았다. 특히, 과학기술의 발전과 군의 전투개념 변화로 요구되는 무기체계도 급속히 변화되면서 자율무인잠수정이 핵심무기체계로 부상하게 되었다. 군에서 효율적인 전장 관리와 사회의 인명 중시 경향은 무기체계를 유인시스템으로 전환시키고 있다. 자율무인잠수정은 심해저 자원탐사, 해양조사 등 민수분야뿐만 아니라 해군의 정보전, 기뢰전, 그리고 대잠전과 같은 성분 작전에서 핵심적 역할을 수행하게 되었다. 본 기고에서 1994년부터 자율무인잠수정 종합발전 계획을 수립하여 개발하고 있는 미 해군 운용개념을 분석하고 분석된 결과를 기초로 하여 미래 우리 해군에서 자율무인잠수정의 개발 및 운용을 위하여 필요한 핵심 기술을 자율제어, 센서 및 신호처리, 진수 및 hgl수. 수중항법, 수중통신, 그리고 에너지 등으로 구분하고 각각에 대하여 기술발전 동향을 고찰하고 기술개발을 제안하였다.

• 로봇학회논문지
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• 제15권1호
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• pp.16-23
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• 2020

This paper describes an alignment algorithm that estimates the initial heading angle of AUVs (Autonomous Underwater Vehicle) for starting navigation in a sea area. In the basic dead reckoning system, the initial orientation of the vehicle is very important. In particular, the initial heading value is an essential factor in determining the performance of the entire navigation system. However, the heading angle of AUVs cannot be measured accurately because the DCS (Digital Compass) corrupted by surrounding magnetic field in pointing true north direction of the absolute global coordinate system (not the same to magnetic north direction). Therefore, we constructed an experimental constraint and designed an algorithm based on extended Kalman filter using only inertial navigation sensors and a GPS (Global Positioning System) receiver basically. The value of sensor covariance was selected by comparing the navigation results with the reference data. The proposed filter estimates the initial heading angle of AUVs for navigation in a sea area and reflects sampling characteristics of each sensor. Finally, we verify the performance of the filter through experiments.