• 대한전기학회논문지:시스템및제어부문D
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• 제55권12호
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• pp.518-525
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• 2006

This paper presents the adaptive robust control method for the flight control systems with model uncertainties. The proposed control system can be composed simply by a combination of the adaptive dynamic surface control (DSC) technique and the self recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides us with the ability to overcome the 'explosion of complexity' problem of the backstepping controller. The SRWNNs are used to observe the arbitrary model uncertainties of flight systems, and all their weights are trained on-line. From the Lyapunov stability analysis, their adaptation laws are induced and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a high performance aircraft (F-16) are utilized to validate the good tracking performance and robustness of the proposed control system.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2006년도 전력전자학술대회 논문집
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• pp.526-528
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• 2006

An adaptive output-feedback neural control problem of SISO strict-feedback nonlinear system is considered in this paper. The main contribution of the proposed method is that it is shown that the output-feedback control of the strict-feedback system can be viewed as that of the system in the normal form. As a result, proposed output-feedback control algorithm is much simpler than the previous backstepping-based controllers. Depending heavily on the universal approximation property of the neural network (NN) only one NN is employed to approximate lumped uncertain nonlinearity in the controlled system.

• 제어로봇시스템학회논문지
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• 제16권3호
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• pp.239-244
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• 2010

This paper is to present map building of mobile robot using RFID (Radio Frequency Identification) technology and ultrasonic sensor. For mobile robot to perform map building, the mobile robot needs its localization and accurate driving in space. In this reason, firstly, kinematic modeling of mobile robot under non-holonomic constrains is introduced. Secondly, based on this modeling, a tracking controller is designed for tracking a given path based on backstepping method using Lyapunov function. The Lyapunov function is also introduced for proving the stability of the designed tracking controller. Thirdly, 2D map building is performed by RFID system, mobile robot system and ultrasonic sensors. The RFID mobile robot system is composed of DC motor, encoder, ultra sonic sensor, digital compass, RFID receiver and RFID antenna. Finally, the path tracking simulation results and map building experimental results are presented to show the effectiveness of the designed controller.

• 전기학회논문지
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• 제60권4호
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• pp.856-861
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• 2011

The mobile robot controller is designed to track the target and to maintain the formation at the same time. Formation control is included in mobile robot controller by extending the trajectory tracking algorithm. The dynamic model of mobile robot is used with kinematic model considering the practical physical parameters of mobile robot. The dynamic model of mobile robot transforms velocity control input of kinematic model into torque control input which is the practical control input of mobile robot. Formation controller of mobile robot is designed to satisfy Lyapunov stability by backstepping method. The designed formation controller is applied to the mobile robot for various target movements and simulated to confirm the Lyapunov stability.

• 한국항공우주학회지
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• 제38권5호
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• pp.437-444
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• 2010

본 논문에서는 한 개의 1축 가변속 CMG를 장착한 부족구동 위성의 자세제어 문제를 다루고 있다. 이러한 부족구동 위성의 경우, 전체 모멘텀이 영(zero)이 아니면 자세를 임의로 취할 수 없다. 위성을 안정화 시키려면 가변속 CMG가 위성의 모멘텀 방향으로 정렬해야 하기 때문이다. 4가지의 다른 장착형상을 고려하였으며, 각각에 대해 제어가능 모멘텀 영역을 분석하였다. 또한 각 형상에 대해 백스테핑 기법을 이용하여 안정한 자세제어 법칙을 제시하고 자세제어 특성을 비교하였다.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2365-2377
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• 2017

This paper addresses two interrelated problems concerning the tracking control of pod propulsion unmanned surface vessel (USV), namely, the modeling of pod propulsion USV, and tracking controller design. First, based on MMG modeling theory, the model of pod propulsion USV is derived. Furthermore, a practical adaptive neural tracking controller is proposed by backstepping technique, neural network approximation and adaptive method. Meanwhile, unlike some existing tracking methods for surface vessel whose control algorithms suffer from "explosion of complexity", a novel neural shunting model is introduced to solve the problem. Using a Lyapunov functional, it is proven that all error signals in the system are uniformly ultimately bounded. The advantages of the paper are that first, the underactuated characteristic of pod propulsion USV is proved; second, the neural shunting model is used to solve the problem of "explosion of complexity", and this is a combination of knowledge in the field of biology and engineering; third, the developed controller is able to capture the uncertainties without the exact information of hydrodynamic damping structure and the sea disturbances. Numerical examples have been given to illustrate the performance and effectiveness of the proposed scheme.

• 한국정밀공학회지
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• 제30권10호
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• pp.1031-1039
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• 2013

This paper presents gain optimization of a 6-DOF underwater robotic platform with 4 rotatable thrusters. To stabilize the 6-DOF motion of the underwater robotic platform, a back-stepping controller is designed with 6 proportional gains and 6 derivative gains. The 12 gains of the backstepping controller are optimized to decrease settling time in step response in 6-DOF motion independently. Stability criterion and overshoots are used as a constraint of the optimization problem. Trust-region algorithm and hybrid Taguchi-Random order Coordinate search algorithm are used to determine the optimal parameters, and the results by two methods are analyzed. Additionally, the resulting controller shows improved performance under disturbances.