• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.180.5-180
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• 2001

This paper presents A Design of WMR Controller that being composed of cooperative relation between PID controller and optimized neural network algorithm, it operate a variable control by velocity. Some proposed algorithm in the past just depended on PID controller for the control of position of WMR but for more efficient control we design a variable controller that operate control by PD controller using neural network if it is satisfied with any given condition. it adjust gain of PD controller for real time control using a fast feedforward algorithm which is different with Form of the standard backpropagation algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.67.1-67
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• 2001

This paper presents a neural network based self-tuning fuzzy PI-PD control scheme for robust speed control of induction motor. The PID controller is being widely used in industrial applications. When continuously used long time, the electric and mechanical parameters of induction motor change, degrading the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, and proposes a neural network based self-tuning fuzzy PI-PD controller whose scaling factors are adjusted automatically. Proposed scheme is simple in structure and computational burden is small ...

• 전자공학회논문지SC
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• 제37권5호
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• pp.46-55
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• 2000

본 논문은 카오틱 신경망과 PD 제어기를 이용한 로봇 시스템의 직접적응제어 방식에 관한 것이다. 카오틱 신경망은 상·하층 결합계수 외에 궤환 결합계수와 동일 층 내의 결합계수를 가지며, 뉴런자체의 충분한 비선형성 때문에 강한 동적특성을 가지고 있다. 그러나 신경망의 구조 및 학습의 문제점으로 인하여 동적 시스템의 제어에 적용되지 못하고 있다. 본 논문에서는 기존의 카오틱 신경망을 제어 분야에 적용하기 위하여 적합한 구조로 수정하고 수정된 신경망의 학습에 관하여 고찰하였다. 제안된 신경망은 모의 실험을 통하여 3 축 푸마 로봇의 경로 제어에 적용하였다. 카오틱 신경망 제어기는 PD 제어기와 병렬로 구성하여 학습 초기의 안정성을 확보하였고, 제어대상의 비선형성을 보상하는 보상 제어기의 역할을 수행하도록 하였다

• Journal of Advanced Marine Engineering and Technology
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• 제33권8호
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• pp.1246-1253
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• 2009

논문은 서보계에 퍼지제어를 위하여 퍼지 $\alpha$-레벨 집합 분해에 기초하한 퍼지추론 계산식이 유도 되었다. 유도한 계산식에 기초한 PI+PD형 퍼지 제어기는 퍼지 추론에서 비퍼지화까지 일체형으로 구성되어 PWM 조작량 u를 발생하는 퍼지 로직 회로가 제안되었다. 시뮬레이션에 의해 퍼지추론의 $\alpha$-레벨의 효과가 검토되어 직류 서보계의 퍼지제어에서 $\alpha$-레벨 양자화수는 4단계이면 충분한 것을 알 수 있다. 제안한 하드웨어 퍼지제어기는 직류 서보계의 위치제어에 시뮬레이션과 실험이 성공적으로 행할 수 있었다.

• 제어로봇시스템학회논문지
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• 제8권3호
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• pp.193-198
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• 2002

In this paper, we Propose a PD+I fuzzy controller using an error-accumulating applying factor. In fuzzy control, analytical study was done formerly, in which fuzzy control can be classified by PD type and PI type, and also the study for getting merits of both types was done, too. But the mixed type has a complex structure and many parameters. The proposed fuzzy controller is 2-input 2-out-put and PD type fuzzy control is used as a basic structure. And the proposed controller annihilates a steady-state error and improves transient responses because of using the error-accumulating applying factor which is determined in the real time along the current state of controlled process. Futhermore it is easy to tune the system because of decreasing the number of scaling factors and the I type controller with resetting resolves the integral wind-up problem. Finally we apply the proposed scheme to various plants and show the performance betterment.

• 융합신호처리학회논문지
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• 제3권1호
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• pp.74-79
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• 2002

많은 제어기법들이 이산시간영역제어계에서 제어성능을 개선하기 위해서 제안되고 있다. 이 제어기법들을 이용한 제어계에서 계의 응답특성은 제어기의 이득에 관계한다. 특히 외란이나 부하변동에 의해서 계의 응답이 변할 때 제어기의 이득을 재조정할 필요가 있다. 본 논문에서는 다층 신경망으로 I-PD제어기와 전치보상기를 설계하였다. I-PD제어기와 전치보상기의 이득이 자동적으로 역전파 알고리즘에 의해서 조정되도록 하였다. 제어계의 응답이 어떤 조건에 의해서 변할 때 I-PD제어기와 전치보상기의 이득들이 역전파 알고리즘에 의해서 자동적으로 조정되게 하였다. 이 I-PD제어기법을 직류 서보 전동기를 구동원으로 하는 위치제어계에 적용하여 제어기의 제어성능을 실험 결과로 타당성을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.428-431
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• 1995

In this paper we propose an on-line tuning method by using genetic algorithm for robust minimax I-PD controller based on new criterion. The new criterion is the Integral of Squared Error (ISE) with a penalty of the derivative of manipulated variable. The work focuses on robust tuning of I-PD controller's parameters in the presence of plant parameter uncertainty. The result of several simulation studies are provided to illustrate the performance of this robust tunig method.

• 제어로봇시스템학회논문지
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• 제16권3호
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• pp.249-255
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• 2010

The paper proposes a new type of robust speed control strategy for permanent magnet synchronous motor by using PD-sliding mode hybrid control. The PD control has a good performance in the transient region while the sliding mode controller provides the robustness against system uncertainties. Taking advantages of the two control strategies, the proposed control method utilizes the PD control in the approaching region to the sliding surface and the sliding mode control near at the sliding surfaces. The chattering problem of the sliding mode controller is eliminated by applying the saturation function for the switching function of the sliding mode control. The stability of the sliding mode control is verified by using Lyapunov function with the proper selection of variable gains. It is shown that with this simple switching algorithm, stability of the overall hybrid control system is ensured. Through the simulations, the PD-sliding mode algorithm is shown to have a good performance in the transient response as well as being robust against disturbances. The robustness of the PD-sliding mode algorithm is further demonstrated against various external disturbances in the real experiments of SPMSM motor control.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.401-405
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• 1993

This paper presents a neuro adaptive control method for nonlinear dynamical systems based on artificial neural network systems. The proposed neuro adaptive controller consists of 3 layers artificial neural network system and parallel PD controller. At the early stage in learning or identification process of the system characteristics the PD controller works mainly in order to compensate for the inadequacy of the learning process and then gradually the neuro contrller begins to work instead of the PD controller after the learning process has proceeded. From the simulation studies the neuro adaptive controller is seen to be robust and works effectively for nonlinear dynamical systems from a practical applicational points of view.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.568-576
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• 1998

In this thesis discuss with a flexible robotic finger design and controller which is used for the micro flexible robotic finger. So, miniaturization, precision, controller for the control of grasping force and actuator were needed. And, even if we develop a new actuator and controller, in order to use on real system, we must considerate of a many side problem. In a force control of micro flexible finger for grasping an object, the fingertip's vibration was more important task of accuracy control. And, controller were adopt the PD/PI mixed type fuzzy controller. The controller were consist of two part, one is a PD type fuzzy controller for increase the rising time response, the other is a PI type fuzzy controller for decrease of steady-state error. Especially, in a PD type fuzzy controller, we used only seven rules. And, for a PI controller, we adopt a reset factor for the control of input values. so, we have overcome the exceed of controller's input range. For the estimate of ontroller's utility and usefulness, we have experiment and computer simulation of three cases. First, we consider of unit force grasping control for a task object, which is 0.03N. Second, bounding grasping force control which is add to a sinusoidal force on the unit force. At this cases the task force is (0.03+0.01 sin wt N). And consider of following of rectangular forces.