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검색결과 402건 처리시간 0.026초

이산형 칼만 필터를 이용한 서보 시스템의 추정자 설계 (Design of an Estimator for Servo Systems using Discrete Kalman Filter)

  • 신두진;허욱열
    • 대한전기학회논문지:전력기술부문A
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    • 제48권8호
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    • pp.996-1003
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    • 1999
  • This paper propose a position-speed controller with an estimator which can estimate states and disturbance. The overall control system consists of two parts: the position-speed controller and an estimator. The Kalman filter applied as state-feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear, unbiased and minimum error variance recursive algorithm to optimally estimate the unknown state. Therefore, we consider the error problem about the servo system modeling and the measurement noise as a stochastic system and implement a optimal state observer, and enhance the estimate performance of position and speed using that. Using two-degree-of freedom(TDOF) conception, we design the command input response and the closed loop characteristics independently. The servo system is to improve the closed loop characteristics without affecting the command imput response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer using a inverse-transfer matrix. Therefore, the performance of overall position-speed controller is enhanced. Finally, the performance of the proposed controller is exemplified by some simulations and by applying the real servo system.

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화학 공정의 제어성의 구조적 분석에 관한 연구 (A Study on the Structural Analysis of Controllability in Chemical Processes)

  • 이병우;김윤식;윤인섭
    • 한국가스학회지
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    • 제3권1호
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    • pp.27-32
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    • 1999
  • 화학 공정은 그 특성상 비선형성이 크고, 다변수 시스템이며, 그 구조가 복잡하다. 그러나 현재까지 개발된 제어성 평가 방법들은 제어성의 평가 방법이 복잡하고, 평가에 필요한 정보가 설계의 초기 단계에서는 알 수 없는 경우가 많다 따라서 공정 및 공장 설계 과정에서 제어성의 평가 및 향상 단계를 적절하게 도입하기 위해서는 이를 위한 절차에 대한 연구가 필요하다. 초기 설계 단계에서의 정보를 이용하여 제어성을 평가하기 위해서는 공정 구조를 분석하는 것이 가장 효율적이다. 입력 변수와 출력 변수가 얼마나 직접적으로 영향을 주는가를 나타내는 척도로는 상대 차수가 있다. 열교환망 합성에서 상대 차수를 이용한 구조적 제어성 분석 방법이 설계 초기 단계에서 효율적임을 알 수 있었다.

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Human Face Tracking and Modeling using Active Appearance Model with Motion Estimation

  • Tran, Hong Tai;Na, In Seop;Kim, Young Chul;Kim, Soo Hyung
    • 스마트미디어저널
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    • 제6권3호
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    • pp.49-56
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    • 2017
  • Images and Videos that include the human face contain a lot of information. Therefore, accurately extracting human face is a very important issue in the field of computer vision. However, in real life, human faces have various shapes and textures. To adapt to these variations, A model-based approach is one of the best ways in which unknown data can be represented by the model in which it is built. However, the model-based approach has its weaknesses when the motion between two frames is big, it can be either a sudden change of pose or moving with fast speed. In this paper, we propose an enhanced human face-tracking model. This approach included human face detection and motion estimation using Cascaded Convolutional Neural Networks, and continuous human face tracking and modeling correction steps using the Active Appearance Model. A proposed system detects human face in the first input frame and initializes the models. On later frames, Cascaded CNN face detection is used to estimate the target motion such as location or pose before applying the old model and fit new target.

DTD 역 구성을 통한 XML문서에서의 정보추출 (Extracting Information from XML Documents by Reverse Generating DTDs)

  • 정종석;오동익
    • 한국멀티미디어학회논문지
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    • 제6권2호
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    • pp.309-318
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    • 2003
  • 분산된 환경에서 정보를 교환하기 위한 수단으로의 XML문서는, 그 자료의 구성을 정의하는 DTD를 통해서만 정확한 의미가 파악될 수 있다. 하지만 인터넷에서 수집된 XML 문서에 항상 DTD가 제공되리라는 보장은 없으며, 이러한 경우에는 수집 된 XML 문서의 구조를 파악한 후 정보를 추출해야 한다. 본 연구에서는 DTD가 알려지지 않은 XML 문서를 바탕으로 적합한 DTD를 구성하고, 이를 이용해 XML 정보를 구조적인 형태로 하부 DB에 저장할 수 있는 방법에 대해 설명하고자 한다. 특히, 본 연구를 통해 개발된 DTD 추출기는 XML 파일을 1-Path로 스캔하기에 기존에 나와있는 다른 방식보다 더 효율적으로 DTD를 구축할 수 있다.

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Mask R-CNN을 이용한 물체인식 및 개체분할의 학습 데이터셋 자동 생성 (Automatic Dataset Generation of Object Detection and Instance Segmentation using Mask R-CNN)

  • 조현준;김다윗;송재복
    • 로봇학회논문지
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    • 제14권1호
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    • pp.31-39
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    • 2019
  • A robot usually adopts ANN (artificial neural network)-based object detection and instance segmentation algorithms to recognize objects but creating datasets for these algorithms requires high labeling costs because the dataset should be manually labeled. In order to lower the labeling cost, a new scheme is proposed that can automatically generate a training images and label them for specific objects. This scheme uses an instance segmentation algorithm trained to give the masks of unknown objects, so that they can be obtained in a simple environment. The RGB images of objects can be obtained by using these masks, and it is necessary to label the classes of objects through a human supervision. After obtaining object images, they are synthesized with various background images to create new images. Labeling the synthesized images is performed automatically using the masks and previously input object classes. In addition, human intervention is further reduced by using the robot arm to collect object images. The experiments show that the performance of instance segmentation trained through the proposed method is equivalent to that of the real dataset and that the time required to generate the dataset can be significantly reduced.

Adaptive Sliding Mode Control based on Feedback Linearization for Quadrotor with Ground Effect

  • Kim, Young-Min;Baek, Woon-Bo
    • 한국정보기술학회 영문논문지
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    • 제8권2호
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    • pp.101-110
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    • 2018
  • This paper introduces feedback linearization (FL) based adaptive sliding mode control (ASMC) effective against ground effects of the quadrotor UAV. The proposed control has the capability of estimation and effective rejection of those effects by adaptive mechanism, which resulting stable attitude and positioning of the quadrotor. As output variables of quadrotor, x-y-z position and yaw angle are chosen. Dynamic extension of the quadrotor dynamics is obtained for terms of roll and pitch control input to be appeared explicitly in x-y-z dynamics, and then linear feedback control including a ground effect is designed. A sliding mode control (SMC) is designed with a class of FL including higher derivative terms, sliding surfaces for which is designed as a class of integral type of resulting closed loop dynamics. The asymptotic stability of the overall system was assured, based on Lyapunov stability methods. It was evaluated through some simulation that attitude control capability is stable under excessive estimation error for unknown ground effect and initial attitude of roll, pitch, and yaw angle of $30^{\circ}$ in all. Effectiveness of the proposed method was shown for quadrotor system with ground effects.

Adaptive second-order nonsingular terminal sliding mode power-level control for nuclear power plants

  • Hui, Jiuwu;Yuan, Jingqi
    • Nuclear Engineering and Technology
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    • 제54권5호
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    • pp.1644-1651
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    • 2022
  • This paper focuses on the power-level control of nuclear power plants (NPPs) in the presence of lumped disturbances. An adaptive second-order nonsingular terminal sliding mode control (ASONTSMC) scheme is proposed by resorting to the second-order nonsingular terminal sliding mode. The pre-existing mathematical model of the nuclear reactor system is firstly described based on point-reactor kinetics equations with six delayed neutron groups. Then, a second-order sliding mode control approach is proposed by integrating a proportional-derivative sliding mode (PDSM) manifold with a nonsingular terminal sliding mode (NTSM) manifold. An adaptive mechanism is designed to estimate the unknown upper bound of a lumped uncertain term that is composed of lumped disturbances and system states real-timely. The estimated values are then added to the controller, resulting in the control system capable of compensating the adverse effects of the lumped disturbances efficiently. Since the sign function is contained in the first time derivative of the real control law, the continuous input signal is obtained after integration so that the chattering effects of the conventional sliding mode control are suppressed. The robust stability of the overall control system is demonstrated through Lyapunov stability theory. Finally, the proposed control scheme is validated through simulations and comparisons with a proportional-integral-derivative (PID) controller, a super twisting sliding mode controller (STSMC), and a disturbance observer-based adaptive sliding mode controller (DO-ASMC).

Smart tracking design for aerial system via fuzzy nonlinear criterion

  • Wang, Ruei-yuan;Hung, C.C.;Ling, Hsiao-Chi
    • Smart Structures and Systems
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    • 제29권4호
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    • pp.617-624
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    • 2022
  • A new intelligent adaptive control scheme was proposed that combines the control based on interference observer and fuzzy adaptive s-curve for flight path tracking control of unmanned aerial vehicle (UAV). The most important contribution is that the control configurations don't need to know the uncertainty limit of the vehicle and the influence of interference is removed. The proposed control law is an integration of fuzzy control estimator and adaptive proportional integral (PI) compensator with input. The rated feedback drive specifies the desired dynamic properties of the closed control loop based on the known properties of the preferred acceleration vector. At the same time, the adaptive PI control compensate for the unknown of perturbation. Additional terms such as s-surface control can ensure rapid convergence due to the non-linear representation on the surface and also improve the stability. In addition, the observer improves the robustness of the adaptive fuzzy system. It has been proven that the stability of the regulatory system can be ensured according to linear matrix equality based Lyapunov's theory. In summary, the numerical simulation results show the efficiency and the feasibility by the use of the robust control methodology.

선형 판별 분석 및 k-means 알고리즘을 이용한 적대적 공격 유형 분류 방안 (An Adversarial Attack Type Classification Method Using Linear Discriminant Analysis and k-means Algorithm)

  • 최석환;김형건;최윤호
    • 정보보호학회논문지
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    • 제31권6호
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    • pp.1215-1225
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    • 2021
  • 인공지능 기술은 우수한 성능을 기반으로 다양한 분야에 적용되고 있지만 입력 데이터에 인간이 감지할 수 없는 적대적 섭동을 추가하여 인공지능 모델의 오작동을 유도하는 적대적 예제에 취약하다. 현재까지 적대적 예제에 대응하기 위한 방법은 세 가지 범주로 분류할 수 있다. (1) 모델 재학습 방법; (2) 입력 변환 방법; (3) 적대적 예제 탐지 방법. 이러한 적대적 예제에 대응하기 위한 방법은 끊임없이 등장하고 있지만 각 적대적 공격 유형을 분류하는 연구는 미비한 실정이다. 따라서, 본 논문에서는 차원 축소와 군집화 알고리즘을 활용한 적대적 공격 유형 분류 방법을 제안한다. 구체적으로, 제안하는 방법은 적대적 예시로부터 적대적 섭동을 추출하고 선형 판별 분석(LDA)를 통해 적대적 섭동의 차원을 축소한 후에 k-means 알고리즘으로 적대적 공격 유형 분류를 수행한다. MNIST 데이터셋과 CIFAR-10 데이터셋을 대상으로 한 실험을 통해, 제안하는 기법은 5개의 적대적 공격(FGSM, BIM, PGD, DeepFool, C&W)을 효율적으로 분류할 수 있으며, 적대적 예제에 대한 정상 입력을 알 수 없는 제한적인 상황에서도 우수한 분류 성능을 나타내는 것을 확인하였다.

페이딩 채널에서 직렬 결합 CPM (SCCPM)에 대한 RS-A-SISO 알고리즘과 확률 밀도 진화 분석 (Density Evolution Analysis of RS-A-SISO Algorithms for Serially Concatenated CPM over Fading Channels)

  • 정규혁;허준
    • 대한전자공학회논문지TC
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    • 제42권7호
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    • pp.27-34
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    • 2005
  • Iterative detection은 additive white Gaussian noise(AWGN) channel의 경우 interleaver들을 포함한 조합유한상태머신(concatenated Finite State Machine)들에 대해 근사적으로 optimal solution에 가깝다는 것이 입증되었습니다. 수신단에서 정확한 채널 상태 정보(perfect channel state information)가 얻어질 수 없는 경우 adaptive Iterative detection이 시간적으로 변하거나 또는 부정확한 채널 변수를 다루기위해 필요합니다. Iterative detection과 adaptive iterative detection대한 기본 building block은 각각 Soft-Input Soft-Output (SISO)와adaptive SISO (A-SISO)입니다. SISO와 A-SISO의 complexity은 state memory나 channel memory에 비례해서 지수적으로 증가합니다. 본 논문에서는 Reduced State SISO (RS-SISO) 알고리즘이 A-SISO의 complexity 감소를 위해 적용되어 fading ISI channel을 통한 serially concatenated CPM의 성능이 adaptive iterative detection을 이용하면 터보 코드 같은 성능을 나타내는 것과 또한 RS-A-SISO system이 큰 iterative detection gain을 가지는 것을 보였습니다. RS-A-SISO 알고리즘에 대한 다양한 design option들의 성능을 평가하였으며 성능과 complexity를 비교하였습니다. 또한 보통 AWGN 채널에서 사용되어지는 density evolution 분석기법이 주파수 선택적인 페이딩 채널에서 RS-A-SISO 시스템에서도 좋은 분석기법임을 보였습니다