• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2551-2554
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• 2003

In this paper, we describe the nonlinear character for a friction control. The nonlinear character of friction control is inherent in mechanical system, which has gained more and more interest. The modeling and compensation of nonlinear friction are difficult tasks for precise motion control. This paper is performance evaluation of nonlinearities and mechanical compliance exists together with friction control system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.38.1-38
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• 2001

In this paper, the vibration suppression problem of an axially moving power transmission belt is investigated. The equations of motion of the moving belt is first derived by using Hamilton´s principle for systems with changing mass. The total mechanical energy of the belt system is considered as a Lyapunov function candidate. Using the Lyapunov second method, a nonlinear boundary control law that guarantees the uniform asymptotic stability is derived. The control performance with the proposed control law is simulated. It is shown that a boundary control can still achieve the uniform stabilization for belt systems.

• 제어로봇시스템학회논문지
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• 제9권5호
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• pp.374-378
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• 2003

A new discrete-time fuzzy output feedback control method for nonlinear systems with unknown time-delay is proposed. Ma et al. proposed an analysis and design method of fuzzy controller and observer and Cao et al. extend this result to be applicable fir the nonlinear systems with known time-delay. For the case of unknown time-delay, we derive the sufficient condition f3r the asymptotic stability of the equilibrium Point by applying Lyapunov-Krasovskii theorem and convert this condition into the LMI problem.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.575-580
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• 2003

In this paper, we develop a control hardware such as an FPGA based general purpose controller with a DSP board to solve nonlinear control problems. PID control algorithms are implemented in an FPGA and neural network control algorithms are implemented in a DSP board. PID controllers implemented on an FPGA was designed by using VHDL to achieve high performance and flexibility. By using high capacity of an FPGA, the additional hardware such as an encoder counter and a PWM generator, can be implemented in a single FPGA device. As a result, the noise and power dissipation problems can be minimized and the cost effectiveness can be achieved. In order to show the performance of the developed controller, it was tested for controlling nonlinear systems such as an inverted pendulum.

• 제어로봇시스템학회논문지
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• 제6권4호
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• pp.247-253
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• 2000

In this paper, we deal with the full range control problem of nonlinear boiler systems subject to complex actuator constraints. Firstly, $H\infty$ loop shaping design procedure［10］ is used for the controller design. Secondly, modified high-gain feedback［11］ for the loop shaping controller is adopted for the anti-windup function and the bumpless transfer technique between controllers is proposed for the full range control of nonlinear systems. Finally, the performance of the proposed controller is demonstrated through the simulation studies.

• 한국지능시스템학회논문지
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• 제7권3호
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• pp.65-71
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• 1997

신경 회로망의 출현으로 비선형 시스템 모델링에 대한 관힘이 다시 고조되고 있다. 따라서 본 논문에서는 미지의 비선형 시스템을 동적으로 인식하기 위해 GMDH(Group Method of Data Handling) 일고리즘을 사용한 DPNN(Dynamic Polynomial Neural Network)을 제안한다. GMDH를 사용한 동적 시스템의 인신은 일렬의 입/출력 데이타를 인가하여 필요한 계수들의 집합을 동적으로 산출함으로써 훈련시킨다. 또한 DPNN을 이용하여 비선형 시스템을 제어하기 위해, MRA(Model Reference Adaptive Control)를 설계한다. 결과에서 컴퓨터 시뮬레이션을 통해 DPNN을 사용한 모델링과 제어가 잘 수행됨을 알 수 있었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.444-444
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• 2000

For a class of nonlinear systems which satisfy a certain condition so called output feedback exponential passivity (OFEP), it is well known that one can easily design a high-gain output feedback control system. The designed high-gain controller has simple structure and high robustness. However, from the viewpoint of practical application, it is important to consider a robust control scheme for controlled systems for which some of the assumptions of output feedback stabilization are not valid. In this paper. we deal with a design problem of the robust high-gain adaptive output feedback control for the above-mentioned class of nonlinear systems with uncertain nonlinearities and/or disturbances.

• 한국산학기술학회논문지
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• 제11권5호
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• pp.1597-1600
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• 2010

본 논문은 비선형 동적 신경망을 이용하여 직접 제어에 관한 연구이다. RBF 신경망을 이용한 제어입력과 근사화 오차 및 외란의 영향을 제거하기 위한 보조제어 입력으로 구성하였다. 외란이나 근사화 오차에 관계없이 플랜트와 기준모델 사이의 오차가 0이 되도록 하는 알고리즘을 구할 수 있었다. 시뮬레이션 결과는 매우 효과적이며 비선형 시스템의 만족스러운 학습 성능을 증명하였다.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2003년도 하계학술대회 논문집
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• pp.177-182
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• 2003

The robust output tracking control problem of general nonlinear MIMO systems is discussed. The robustness against parameter uncertainties is considered. In this paper, we proposed the robust output tracking control scheme for a class of MIMO nonlinear dynamical systems using output feedback linearization method. The presented control scheme is based on the VSS. We assume that the nonlinear dynamical system is minimum phase, the relative degree of the system is r$_{1}$＋r$_{2}$＋…r$_{m}$$\leq$ n and zero dynamics is stable. It is shown that the outputs of the closed-loop system asymptotically track given output trajectories despite the uncertainties while maintaining the boundedness of all signals inside the loop. And we verified that the proposed control scheme is then applied to the control of a two degree of freedom (DOF) robotic manipulator with payload.d.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.621-623
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• 2000

In this paper, the effective design method of the predictive controller using fuzzy neural networks(FNNs) is presented for the Intelligent control of chaotic nonlinear systems. In our design method of controller, predictor parameters are tuned by the error value between the actual output of a chaotic nonlinear system and that of a fuzzy neural network model. And the parameters of predictive controller using fuzzy neural network are tuned by the gradient descent method which uses control error value between the actual output of a chaotic nonlinear system and the reference signal. In order to evaluate the performance of our controller, it is applied to the Duffing system which are the representative continuous-time chaotic nonlinear systems and the Henon system which are representative discrete-time chaotic nonlinear systems.