• 제목/요약/키워드: Output Trajectory Tracking

검색결과 51건 처리시간 0.03초

비 간섭 슬라이딩모드제어에 관한 연구 (A Study on the Decoupling Sliding Mode Control)

  • 박재식;노영오;안병원;남택근
    • Journal of Advanced Marine Engineering and Technology
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    • 제28권7호
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    • pp.1152-1158
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    • 2004
  • In this paper, a trajectory tracking problems using SMC(sliding mode control) is presented. In the conventional method. SMC has been applied to linear systems and the output matrix C has to satisfy a restrictive condition that CB is nonsingular. Under suitable assumptions, decoupling SMC can be adapted to remove the restriction mentioned above. The Proposed control strategy is applied to trajectory tracking control and simulations results are given to demonstrate the effectiveness of the proposed control scheme.

Tip Position Control of a Flexible-Link Manipulator with Neural Networks

  • Tang Yuan-Gang;Sun Fu-Chun;Sun Zeng-Qi;Hu Ting-Liang
    • International Journal of Control, Automation, and Systems
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    • 제4권3호
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    • pp.308-317
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    • 2006
  • To control the tip position of a flexible-link manipulator, a neural network (NN) controller is proposed in this paper. The dynamics error used to construct NN controller is derived based on output redefinition approach. Without the filtered tracking error, the proposed NN controller can still guarantee the closed-loop system uniformly asymptotically stable as well as NN weights bounded. Furthermore, the tracking error of desired trajectory can converge to zero with the proposed controller. For comparison an NN controller with filtered tracking error is also designed for the flexible-link manipulator. Finally, simulation studies are carried out to verify the theoretic results.

반복학습에 의한 MIMO Nonminimum Phase 자율주행 System의 Feedforward 입력신호 생성에 관한 연구 (Feedforward Input Signal Generation for MIMO Nonminimum Phase Autonomous System Using Iterative Learning Method)

  • 김경수
    • 한국군사과학기술학회지
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    • 제21권2호
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    • pp.204-210
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    • 2018
  • As the 4th industrial revolution and artificial intelligence technology develop, it is expected that there will be a revolutionary changes in the security robot. However, artificial intelligence system requires enormous hardwares for tremendous computing loads, and there are many challenges that need to be addressed more technologically. This paper introduces precise tracking control technique of autonomous system that need to move repetitive paths for security purpose. The input feedforward signal is generated by using the inverse based iterative learning control theory for the 2 input 2 output nonminimum-phase system which was difficult to overcome by the conventional feedback control system. The simulation results of the input signal generation and precision tracking of given path corresponding to the repetition rate of extreme, such as bandwidth of the system, shows the efficacy of suggested techniques and possibility to be used in military security purposes.

반복학습 제어를 사용한 신경회로망 제어기의 구현 (Realization of a neural network controller by using iterative learning control)

  • 최종호;장태정;백석찬
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.230-235
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    • 1992
  • We propose a method of generating data to train a neural network controller. The data can be prepared directly by an iterative learning technique which repeatedly adjusts the control input to improve the tracking quality of the desired trajectory. Instead of storing control input data in memory as in iterative learning control, the neural network stores the mapping between the control input and the desired output. We apply this concept to the trajectory control of a two link robot manipulator with a feedforward neural network controller and a feedback linear controller. Simulation results show good generalization of the neural network controller.

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최적의 Bang-Bang 입력을 이용한 볼-빔 시스템의 강인한 추적 제어 (Robust Tracking Control of a Ball and Beam System using Optimal Bang-Bang Input)

  • 이경태;최호림
    • 전기전자학회논문지
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    • 제22권1호
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    • pp.110-120
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    • 2018
  • 본 논문에서는, 볼-빔 시스템에 입-출력 궤환 선형화 기법을 적용하여 추종 궤적 r(t)를 추종하도록 제어기를 설계하였다. 설계한 제어기로 시뮬레이션 및 실험에 적용한 결과, 실험에서 오차가 크게 발생하였다. 이러한 이유는 외란 및 입력정합조건을 만족하지 못해 발생한 것으로 판단되어 볼-빔 시스템의 기존 모델링에서 적절한 외란을 추가하여, 시뮬레이션을 통해 실험 결과와 비슷한 유효한 모델링임을 입증하였다. 그러나, 여전히 저하된 성능으로 인해 bang-bang 제어기를 추가로 적용하였다. 결과적으로, 시스템의 불확실성에 대해 강인하고 향상된 성능을 시뮬레이션 및 실험결과를 통해 검증하였다.

포토센서를 이용한 태양위치 추적기의 성능분석에 관한 연구 (Performance Evaluation of a Solar Tracking PV System with Photo Sensors)

  • 정병호;조금배;이강연
    • 조명전기설비학회논문지
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    • 제27권5호
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    • pp.67-73
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    • 2013
  • The conversion of solar radiation into electrical energy by Photo-Voltaic (PV) effect is a very promising technology, being clean, silent and reliable, with very small maintenance costs and small ecological impact. The output power produced by the PV panels depends strongly on the incident light radiation. The continuous modification of the sun-earth relative position determines a continuously changing of incident radiation on a fixed PV panel. The point of maximum received energy is reached when the direction of solar radiation is perpendicular on the panel surface. Thus an increase of the output energy of a given PV panel can be obtained by mounting the panel on a solar tracking device that follows the sun trajectory. Tracking systems that have two axes and follow the sun closely at all times during the day are currently the most popular. This paper presents research conducted into the performance of Solar tracking system with photosensors. The results show that an optimized dual-axis tracking system with photosensor performance and analysis. From the obtained results, it is seen that the sun tracking system improves the energy and energy efficiency of the PV panel.ti-junction CPV module promises to accelerate growth in photovoltaic power generation.

로봇 매니퓰레이터의 불확실성 보상을 위한 퍼지­-뉴로 제어 (A Fuzzy-Neural Control for Uncertainty Compensation of Robot Manipulator)

  • 박세준;양승혁;황문구;양태규
    • 한국정보통신학회논문지
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    • 제7권8호
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    • pp.1759-1766
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    • 2003
  • 본 논문에서는 로봇 매니퓰레이터의 궤적 추종 제어에 관한 연구를 위하여 뉴로­퍼지 제어기를 제안하였다. 궤적 추종 제어기를 설계할 경우, 주로 이용되는 효과적인 방법은 토크 계산 제어 방식이다. 그러나, 로봇 매니퓰레이터에 의한 불확실성 문제로 인하여 토크 계산 제어 방식만으로는 좋은 제적 추종 성능을 얻을 수가 없다. 그러므로, 본 논문에서는 로봇 매니퓰레이터에서 발생한 불확실성을 보상하기 위하여 제안된 뉴로­퍼지 제어기를 이용하였다. 뉴로­퍼지 제어기에서의 퍼지 규칙의 수를 49개로 설정하였으며, 2관절 로봇 매니퓰레이터를 이용한 컴퓨터 시뮬레이션을 통해 제어기의 효율성을 입증하였다. 그 결과. 제안된 뉴로­퍼지 제어기의 출력이 로봇 매니퓰레이터에서 발생한 불확실성을 효과적으로 감소시킬 수 있음을 확인할 수 있었다.

모터 동역학을 포함한 이동 로봇의 추종 제어를 위한 동적 표면 제어 (Dynamic surface control for trajectory tracking of mobile robots including motor dynamics)

  • 박봉석;최윤호;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 제39회 하계학술대회
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    • pp.1685-1686
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    • 2008
  • Almost all existing controllers for nonholonomic mobile robots are designed without considering the motor dynamics. This is because the presence of the motor dynamics increases the complexity of the system dynamics, and makes difficult the design of the controller. In this paper, we propose a simple controller for trajectory tracking of mobile robots including motor dynamics. For the simple controller design, the dynamic surface control methodology is applied and extended to multi-input multi-output systems (i.e., mobile robots) that the number of inputs and outputs are different. Finally, simulation results demonstrate the effectiveness of the proposed controller.

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Exponential Convergence of A Learning Scheme for Unknown Linear Systems

  • Kuc, Tae-yong;Lee, Jin-Soo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.550-554
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    • 1992
  • In this paper the issue of convergence rate is introduced for a learning control scheme we have developed and applied for tracking of unknown linear systems. A sufficient condition under which the output trajectory converges exponentially fast is obtained using the controllability grammian of controllable linear systems. Under the same condition it is also shown that the learning control input converges exponentially with the same rate as the rate of output convergence. A numerical example with computer simulation results is presented to show the feasibility of the scheme.

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불변 집합을 이용한 컨버터의 입력 제약 추종 제어 (Input-constrained Tracking Control of a Converter Model Using Invariant Sets)

  • 김정수;이영일
    • 제어로봇시스템학회논문지
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    • 제19권3호
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    • pp.177-182
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    • 2013
  • This paper proposes an input-constrained reference tracking control of a converter model. To this end, first it is shown that the bilinear converter model can be equivalently represented by a linear uncertain model belonging to a polytopic set. Then, an input-constrained tracking control scheme for the linear uncertain model is designed based on recently proposed tracking control scheme. The control scheme yields not only a stabilizing control gain but also a feasible and invariant set for the converter model. Finally, simulation results show that the state trajectory always stays in the feasible and invariant set and that the output tracks the given reference while satisfying the input constraint.