• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권4호
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• pp.236-241
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• 2007

This paper presents an adaptive controller using chaotic dynamic neural networks(CDNN) for nonlinear dynamic system. A new dynamic backpropagation learning method of the proposed chaotic dynamic neural networks is developed for efficient learning, and this learning method includes the convergence for improving the stability of chaotic neural networks. The proposed CDNN is applied to the system identification of chaotic system and the adaptive controller. The simulation results show good performances in the identification of Lorenz equation and the adaptive control of nonlinear system, since the CDNN has the fast learning characteristics and the robust adaptability to nonlinear dynamic system.

• 전자공학회논문지 IE
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• 제46권4호
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• pp.73-77
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• 2009

본 논문에서는 모바일 로봇의 경로 주총 제어에 관해 다룬다. 설계된 제어기는 운동학 제어기와 동역학 제어기로 구성된다. 운동학 제어기는 2개의 게인을 가짐에 따라 기존의 3개의 게인을 가지는 제어기에 비해 게인 설정에 필요한 시간을 줄일 수 있다. 동역학 제어기는 마찰력과 외란 보상을 고려하여 다양한 환경에서 경로 추종 성능을 개선시킬 수 있다. 모의실험 결과를 통해 제안된 제어기의 안정된 성능을 확인할 수 있다.

• 동력기계공학회지
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• 제5권4호
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• pp.90-96
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• 2001

In this study, a robust controller to control pressure in a pneumatic pressure vessel considering dynamic characteristics of pneumatic transmission line is proposed. Dynamic characteristics of transmission line using compressible fluid is changed by the flowing states of the fluid. So, if the fixed gain controller is designed based on a fixed model, the performance of the control system could be destabilized or degraded. The controller designed in this study is composed of two parts. The one is to reject modelling error based on the disturbance observer, the other is to obtain the control performance. The control results with the designed controller show that the robustness of the control system is achieved regardless of the change of the model of the transmission line. Therefore, the designed controller can be utilized for the performance improvement of the pressure control system using compressible fluid such as air and gas

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 춘계학술대회논문집
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• pp.715-718
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• 2002

A control strategy for a dynamic system under Irregular disturbance by using stochastic controller is developed. In order to design stochastic controller. system dynamic model in real domain is transformed dynamic moment equation in stochastic domain by F-P-K approach. A study of real time control technique for stochastic controller is presented. The performance of stochastic controller is verified through experiment used by real time control technique method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.75.4-75
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• 2001

This paper designs the robust hybrid controller for the multi degree-of-freedom system having uncertainty caused by modeling error and disturbances. The controlled plant is the construction which has an active dynamic vibration absorber on the top and is excited by the El Centre earthquake at the base. The active controller designed by the LQR(Linear Quadratic Regulator) and H-infinity control theory. The robustness of the hybrid H$\infty$ controller is compared with that of the hybrid LQ controller from computer simulation.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.583-586
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• 2003

There are electric four-wheeled vehicles to assist elder people. Because of the vehicles'dynamic characteristic such as impossible to move abeam, it is difficult for these people who has little experience and has little knowledge to drive. Also to judge the future state of dynamic obstacles and to decide how to elude them safely are more difficult. We installed the predictive fuzzy controller(evaluates the future states which several kinds of operation candidates were done and chooses the best one) that modeled humans'algorithms in the system. Human predicts the future states of dynamic obstacles and chooses an operation(wait, steer, go back, etc) to elude safely. To elude dynamic obstacles flexibly, we added expert's knowledge for safe driving to this controller. In this paper, we propose the intelligent soft driving system by the controller that can elude dynamic obstacles safely, and we confirm the effectiveness by a simulation.

• Journal of Power Electronics
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• 제16권2호
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• pp.564-571
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• 2016

This study proposes an adaptive neuro-fuzzy inference system (ANFIS)-based rotor position controller for brushless direct current (BLDC) motors to improve the control performance of the drive under transient and steady-state conditions. The dynamic response of a BLDC motor to the proposed ANFIS controller is considered as standard reference input. The effectiveness of the proposed controller is compared with that of the proportional integral derivative (PID) controller and fuzzy PID controller. The proposed controller solves the problem of nonlinearities and uncertainties caused by the reference input changes of BLDC motors and guarantees a fast and accurate dynamic response with an outstanding steady-state performance. Furthermore, the ANFIS controller provides low torque ripples and high starting torque. The detailed study includes a MATLAB-based simulation and an experimental prototype to illustrate the feasibility of the proposed topology.

• 전자공학회논문지C
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• 제35C권5호
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• pp.41-49
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• 1998

This paper deals with the self-excited oscillation of a system that is controlled by a dynamic nonlinear fuzzy controller. The self-excited oscillation can be observed in the systems composed of nonlinear elements and its analysis is as important as that of stability in the design of nonlinear systems. by using the frequency transfer function analysis known as the describing function method in nonlinear control theory, the oscillation is theoretically predicted. First, the describing function of a dynamic fuzzy controller is derived and then, based on the derived describing fuction, self-excited oscillation of the system controlled by a dynamic fuzzy controller is predicted. To obtain the describing function of the dynamic fuzzy controller, a simple structure is assumed for the fuzzy controller.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 추계종합학술대회 논문집
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• pp.716-719
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• 1999

In this paper, a real-time control system for robot manipulator is implemented using real-time operating system with capabilities of multitasking, intertask communication and synchronization, event-driven, priority-driven scheduling, real-time clock control, etc. The hardware system with VME bus and related devices is developed and applied to implement a dynamic learning control scheme for robot manipulator. Real-time performance of the proposed dynamic learning controller is tested for tasks of tracking moving objects and compared with the conventional servo controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.279-281
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• 2006

In this paper, we study an approach to design a self-tuning Fuzzy-PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of conversional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. The above problems are solved by adapting Fuzzy-PI controller for the fire angle control of rectifier.[7] The performance of the Fuzzy-PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain the optimal scaling factors of the Fuzzy-PI controller by Genetic Algorithms. In order to improve Fuzzy-PI controller, we adopt FIS to tune the scaling factors of the Fuzzy-PI controller on line. A comparative study has been performed between Fuzzy-PI and self-tuning Fuzzy-PI controller, to prove the superiority of the proposed scheme.