• Title/Summary/Keyword: 강인적응 제어기

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An Adaptive Fuzzy Backstepping Approach to Robust Tracking Control of a Single-Link Flexible Joint Robot (적응형 퍼지 백스테핑 방식을 이용한 단일축 유연관절 로봇의 강인 제어)

  • 김은태;이희진
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.41 no.4
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    • pp.1-12
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    • 2004
  • This paper presents an adaptive fuzzy backstepping (AFB) controller for a single-link flexible joint robot in the Presence of Parametric uncertainties and external disturbances. Adaptive fuzzy logic systems are used as universal approximators to counteract the model uncertainties coming from robot dynamics and to compensate for the nonlinearities coming from adaptive backstepping method. The approach suggested herein does not require neither an additional supervisory nor a robustifying controller and guarantees that tracking error is uniformly ultimately bounded (UUB) within a sufficiently small residual set. Finally, a simulation result is given to demonstrate the robust tracking performance of proposed design method.

An Adaptive Learning Method of Fuzzy Hypercubes using a Neural Network (신경망을 이용한 퍼지 하이퍼큐브의 적응 학습방법)

  • Jae-Kal, Uk;Choi, Byung-Keol;Min, Suk-Ki;Kang, Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.6 no.4
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    • pp.49-60
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    • 1996
  • The objective of this paper is to develop an adaptive learning method for fuzzy hypercubes using a neural network. An intelligent control system is proposed by exploiting only the merits of a fuzzy logic controller and a neural network, assuming that we can modify in real time the consequential parts of the rulebase with adaptive learning, and that initial fuzzy control rules are established in a temporarily stable region. We choose the structure of fuzzy hypercubes for the fuzzy controller, and utilize the Perceptron learning rule in order to upda1.e the fuzzy control ru1c:s on-line with the output errors. As a result, the effectiveness and the robustness of this intelligent controller are shown with application of the proposed adaptive fuzzy-neuro controller to control of the cart-pole system.

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Development of Robust Adaptive Learning Control for Nonlinear System (비선형 시스템에 대한 강인성 적응 학습 제어기의 개발)

  • Yu, Yeong-Sun;Ha, Hwan-Su
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.25 no.12
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    • pp.1895-1902
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    • 2001
  • This paper gives an overview of the relationships between methods of loaming and adaptive control. It is the objective of this paper to develop adaptive learning control algorithms that combine the advantages of adaptive control with those of leaning control to the extent possible for the type of system model used. The robustness of this adaptive loaming control with respect to reinitialization errors and fluctuation of dynamics from disturbance is analyzed extensively. Simulation results have shown to verify the effectiveness of the proposed control algorithm.

A Study on the Adaptive Fuzzy Nonlinear VSS (비선형 슬라이딩 면을 가지는 적응 퍼지 제어기 설계)

  • 이대식;김혜경
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.9
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    • pp.788-792
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    • 2001
  • Although the general sliding model control has the robust property, bounds on the disturbances and parameter variations should be known a prior to the designer of the control system. However, these bounds may not be easily obtained. Fuzzy logic provides an effective way to design a controller of the system with disturbances and parameter variations. Therefore, combination of the best feature of the fuzzy logic control and the sliding mode control is considered. In this paper, the adaptive fuzzy variable structure controller developed for variables of fuzzy logic. A variable length pendulum system is used to demonstrate the availability of the proposed algorithm.

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A New Adaptive Fuzzy Approach for Control of a Bipedal Robot (이족 보행 로봇 제어에 대한 새로운 적응 퍼지 접근방법)

  • Hwang, Jae-Pil;Kim, Eun-Tai
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.42 no.5 s.305
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    • pp.13-18
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    • 2005
  • Over the last few years, the control of bipedal robot has been considered a promising but difficult research field in the community of robotics. In this paper, a new robust output control method for a bipedal robot is proposed using the adaptive fuzzy logic. The adaptive fuzzy logic is used as an system approximator to cancel the unknown uncertainty. First, a model for a bipedal robot including switching leg influence, uncertainty and disturbance is presented. Second, a controller is designed in which the joint velocity measurement is not required. Fuzzy approximation error estimator is inserted in the system for tuning the fuzzy logic. Finally, the result of the computer simulation is presented to show the validity of the suggested control method.

Robust Adaptive Control for Robot Manipulator (로보트 매니퓰레이터의 강인한 적응제어)

  • Yi, Taek-Chong;Ko, Myoung-Sam
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.27 no.10
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    • pp.34-43
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    • 1990
  • An improved parameter adaptation and control law for robot manipulator are proposed based on a linearized parametric system equation and augmented error vectors. In view of the modeling error and parasitics with small time constants which inevitably introduced during modelling process, their effects on the robustness of the system performance are reviewed and as an conutermearsure, adaptation mechanism with low pass filter is proposed. Proposed parameter adaptation and control low assure the stability of the robot manipulator in the large without further assumption. Computer simulation shows its effectiveness of the proposed adaptation mechanism to improve the robustness of the system in presence of the parasitics in the system and superior performance for high speed operations make it an attractive option in application of the adaptive control field for robot manipulator.

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A Study of Adaptive Load Torque Observer and Robust Precision Position Control of BLDD Motor (직접 구동용 BLDC 전동기의 정밀 Robust 위치제어 및 적응형 외란 관측기 연구)

  • 고종선;윤성구
    • The Transactions of the Korean Institute of Power Electronics
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    • v.4 no.2
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    • pp.138-143
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    • 1999
  • A new control method for the precision robust position control of a brushless DC(BLDC) motor for direct drive m motor(BLDDM) system using the asymptotically stable adaptive load torque observer is presented. A precision position c control is obtained for the BLDD motor system appro성mately linearized using the fieldlongrightarroworientation method. Many of t these motor systems have BLDD motor to obtain no backlashes. On the other hand, it has disadvantages such as the h high cost and more complex controller caused by the nonlinear characteristics. And the load torque disturbance is d directly affected to a motor shaft. To r밍ect this problem, stability analysis is calTied out using Lyapunov stability t theorem. Using this results, the stability is proved and load disturbance detected by the asymptotically stable adaptive observer is compensated by feedforwarding the equivalent CUlTent having the fast response.

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High Performance Control of Container Crane using Adaptive-Fuzzy Control (적응 퍼지제어를 이용한 컨테이너 크레인의 고성능제어)

  • Jung, Dong-Hwo;Kim, Do-Yun;Jung, Byung-Jin
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.23 no.2
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    • pp.115-124
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    • 2009
  • This paper proposed an adaptive fuzzy controller for controlling speed and positions of a container crane. The motor used in container crane is installed as SynRM with variable-speed drive having the robustness on the problems of energy and environment. The conventional PI controller is not able to accurately track the position, speed and sway angle of trolley due to the factors of environment and the parameter variety. In the paper, we analyzed the performance of SynRM derive applied to the container crane by using an adaptive fuzzy control of SynRM in order to solve those problems. This paper analyzed the characteristics of position and speed response and compared the performance of PI controller with an adapative Fuzzy controller, proving the validity.

Robust adaptive controller design for robot manipulators (로봇 매니퓰레이터에 대한 강인한 적응 제어기의 설계)

  • Jung, Seok-Woo;Lyou, Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.889-894
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    • 1993
  • This paper presents a robust adaptive control scheme based on the Lyapunov design for robot manipulators subjected to inertial parameter uncertainties and bounded torque disturbances. The scheme is a modified version of the adaptive computed torque method which adopts a dead zone into the adaptation mechanism so as to avoid parameter drifts by disturbances. It is shown via stability analysis and computer simulations that all the signals in the overall adaptive system are bounded and tracking errors lie within a prespecified bound.

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Using GA-FSMC for Precise Water Level Control of Double Tank (GA-FSMC를 이용한 이중탱크의 정밀한 수위 제어)

  • 권용범;박현철;정종원;이준탁
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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    • pp.131-134
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    • 2002
  • 일반적인 산업현장에서 많이 사용되는 이중탱크 시스템은 동작점 근방에서 선형화하는 고전제어기법을 사용한 것으로서 큰 시간지연과 비선형성으로 인해 정확한 수학적 모델링이 어렵고 모델링을 하더라도 넓은 동작 영역에서 만족스로운 결과를 얻기 어렵다. 따라서, 비교적 모델링에 대한 의존도가 낮은 퍼지, 신경회로망, 유전알고리즘 등의 지능제어 기법들도 제안되고 있다. 그러나 이들 제어기 역시 외란이나 다양한 동작 모드들에 따른 제어기 변수들의 적응성 저하로 인해 안정화 가능 영역이 협소해 지는 것은 물론 시스템의 불안정 현상도 초래한다. 이에 반해, SMC(sliding mode controller)는 변수의 변동, 외란에 둔감한 강점을 갖고 있지만, 시스템의 상태에 따른 슬라이딩 평면 설정의 곤란성과 채터링(chattering)이 존재하는 문제점 이 있다. 따라서 본 논문에서는 이중 탱크 시스템의 정밀한 수위 제어를 위하여, GA과 FLC를 사용하여 최적 변수로 설정 할 수 있게 하고, 채터링 저감을 위해 시스템 동특성 변동과 외란 에 강인한 GA-FSMC(genetic algorithm fuzzy sliding mode controller)를 제안하였다. 시뮬레이션을 통해 종래의 제어기의 제어결과와 비교함으로써 제안하는 GA-FSMC의 우수성을 입증하고자 한다.