• 제목/요약/키워드: Robust tracking performance

검색결과 439건 처리시간 0.023초

개선된 유전 알고리즘 기반의 휴머노이드 로봇의 안정 보행을 위한 제어기 구현 (Implementation of the Controller for a Stable Walking of a Humanoid Robot Using Improved Genetic Algorithm)

  • 공정식;이응혁;김진걸
    • 제어로봇시스템학회논문지
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    • 제13권5호
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    • pp.399-405
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    • 2007
  • This paper deals with the controller for a stable walking of a humanoid robot using genetic algorithm. A humanoid robot has instability during walking because it isn't fixed on the ground, and its nonlinearities of the joints increase its instability. If controller isn't robust, the robot may fall down at the ground during walking because of its nonlinearities. To solve this problem, robust controller is required to reduce the effect of nonlinearities and to gain the good tracking performance. In this paper, motion controller that is based on fuzzy-sliding mode controller is proposed. This controller can remove the effect of the saturation by limitation of the input voltage. It also includes compensator for reducing the effect of the nonlinearity by backlash and PI controller improving the tracking performance. In here, genetic algorithm is used for searching the optimal gains of the controller. From the given controller, a humanoid robot can moved more preciously. All the processes are investigated through simulations and are verified experimentally in a real joint system for a humanoid robot.

외란보상기를 이용한 영구자석 동기전동기에 대한 참조모델 견실적응제어기의 성능개선 (Performance Enhancement of RMRAC Controller for Permanent Magnent Synchronous Motor using Disturbance compensator)

  • 김홍철;임훈;이장명
    • 전기학회논문지
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    • 제57권5호
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    • pp.845-851
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    • 2008
  • A simple RMRAC (Robust Model Reference Adaptive Control) scheme for the PMSM (Permanent Magnent Synchronous Motor) is proposed in the synchronous frame. A current control of PMSM is the most inner loop of electro-mechanical driving systems and it requires a fast and simple control law to play a foundation role in the control hierarchy. In the proposed synchronous current model, the input signal is composed of a calculated voltage by proposed adaptive laws and real system disturbance. The gains of feed-forward and feedback controllers are estimated by the proposed modified Gradient method respectively, where the system disturbances are assumed as filtered current tracking errors. After the estimation of the system disturbances from the tracking errors, the corresponding voltage is fed forward to control input voltage to compensate for the disturbances. The proposed method is robust against high frequency disturbance and has a fast dynamic response. It also shows a good real-time performance due to it's simplicity of control structure. Through the simulations and real experiments, efficiency of the proposed method is verified.

인지로봇 청각시스템을 위한 의사최적 이동음원 도래각 추적 필터 (Quasi-Optimal Linear Recursive DOA Tracking of Moving Acoustic Source for Cognitive Robot Auditory System)

  • 한슬기;나원상;황익호;박진배
    • 제어로봇시스템학회논문지
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    • 제17권3호
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    • pp.211-217
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    • 2011
  • This paper proposes a quasi-optimal linear DOA (Direction-of-Arrival) estimator which is necessary for the development of a real-time robot auditory system tracking moving acoustic source. It is well known that the use of conventional nonlinear filtering schemes may result in the severe performance degradation of DOA estimation and not be preferable for real-time implementation. These are mainly due to the inherent nonlinearity of the acoustic signal model used for DOA estimation. This motivates us to consider a new uncertain linear acoustic signal model based on the linear prediction relation of a noisy sinusoid. Using the suggested measurement model, it is shown that the resultant DOA estimation problem is cast into the NCRKF (Non-Conservative Robust Kalman Filtering) problem [12]. NCRKF-based DOA estimator provides reliable DOA estimates of a fast moving acoustic source in spite of using the noise-corrupted measurement matrix in the filter recursion and, as well, it is suitable for real-time implementation because of its linear recursive filter structure. The computational efficiency and DOA estimation performance of the proposed method are evaluated through the computer simulations.

Q-Learning을 사용한 로봇팔의 SMCSPO 게인 튜닝 (Gain Tuning for SMCSPO of Robot Arm with Q-Learning)

  • 이진혁;김재형;이민철
    • 로봇학회논문지
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    • 제17권2호
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    • pp.221-229
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    • 2022
  • Sliding mode control (SMC) is a robust control method to control a robot arm with nonlinear properties. A high switching gain of SMC causes chattering problems, although the SMC allows the adequate control performance by giving high switching gain, without the exact robot model containing nonlinear and uncertainty terms. In order to solve this problem, SMC with sliding perturbation observer (SMCSPO) has been researched, where the method can reduce the chattering by compensating the perturbation, which is estimated by the observer, and then choosing a lower switching control gain of SMC. However, optimal gain tuning is necessary to get a better tracking performance and reducing a chattering. This paper proposes a method that the Q-learning automatically tunes the control gains of SMCSPO with an iterative operation. In this tuning method, the rewards of reinforcement learning (RL) are set minus tracking errors of states, and the action of RL is a change of control gain to maximize rewards whenever the iteration number of movements increases. The simple motion test for a 7-DOF robot arm was simulated in MATLAB program to prove this RL tuning algorithm. The simulation showed that this method can automatically tune the control gains for SMCSPO.

Robust Control of Induction Motor with HTheory based on Loopshaping

  • Benderradji, Hadda;Chrifi-Alaoui, Larbi;Mahieddine-Mahmoud, Sofiane;Makouf, Abdessalam
    • Journal of Electrical Engineering and Technology
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    • 제6권2호
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    • pp.226-232
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    • 2011
  • The $H_{\infty}$ approach, adopted in this paper, is based on loop shaping using a normalized coprime factor combined with a field-oriented control to control induction motor. We develop two loops. The first one, the inner loop, controls the stator current by $H{\infty}$ controller in order to obtain good performance. The second loop, the outer one, guarantees stability and tracking performance of speed and rotor flux using a proportional integral controller. When the rotor flux cannot be measured, we introduce a flux observer to estimate the rotor flux. Simulation and experimental results are presented to validate the effectiveness and the good performance of this control technique.

PD-슬라이딩 모드 복합 제어기를 이용한 로봇 매니퓰레이터의 제어 (Control of Robot Manipulators Using PD-Sliding Mode hybrid Controller)

  • 이규준;경태현;김종식
    • 제어로봇시스템학회논문지
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    • 제8권2호
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    • pp.89-96
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    • 2002
  • A new chattering free PD-sliding mode hybrid control scheme is proposed for robot manipulators. This hybrid controller is composed of a PD controller and a semi-continuous sliding mode controller. It has a good robust performance in reaching mode which does not possess invariance property of sliding mode, and has chattering free characteristics in sliding mode. Thus, the PD-sliding mode hybrid controller has a good robust performance in the whole region. It is shown that the proposed control has a good transient response and trajectory tracking performance for a 2-link SCARA robot manipulator.

이중 구조의 파티클 필터를 이용한 강인한 위치추적 (Robust Location Tracking Using a Double Layered Particle Filter)

  • 윤근호;김대진;방승양
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제33권12호
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    • pp.1022-1030
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    • 2006
  • 위치 인식은 유비쿼터스 컴퓨팅 환경상의 중요한 부분이지만 많은 연구에도 불구하고 아직 완벽한 시스템은 존재하지 않는 상황이다. 본 연구에서는 다양한 위치 추적 시스템 중 가장 널리 사용되는 RFID 시스템을 이용하지만 수신된 RSSI 신호는 리더와 태그 안테나의 방향, 각도, 간섭에 매우 민감하여 기존 알고리즘인 파티클 필터를 이용하면 정확한 위치 추정이 힘들다. 이를 극복하기 위해, 본 연구에서는 이중 구조의 파티클 필터를 가진 강인한 위치 추적 시스템을 제안한다. 이 시스템은 하단부에서 회귀분석이나 SVM 분류기법을 이용하여 대략적인 위치를 확인한 다음, 상단부에서 파티클 필터를 이용하여 위치, 속도, 방향을 추정하는 계층적 구조를 갖고 있다. 그리고 계층 구조상에 움직임 특성이 갖는 여러 제약 사항을 반영하여 위치 추정 성능을 향상시킨다. 제안한 위치 추정 시스템을 실제 상황에 적용하고자 리더와 서버간을 스타 메쉬 네트워크로 연결하여 태그를 소지한 사람과 물체의 위치를 제안한 알고리즘을 이용하여 추정하였다. 실험 결과 제안한 위치 추적 시스템이 기존의 파티클 필터를 이용한 시스템보다 정확한 위치 추정 성능을 보임을 확인하였고 지하 시설물이 복잡하게 놓여있는 매우 열악한 운영 환경상에서도 실시간 동작을 통해 그 유용성이 입증되었다.

A LOCALIZED GLOBAL DEFORMATION MODEL TO TRACK MYOCARDIAL MOTION USING ECHOCARDIOGRAPHY

  • Ahn, Chi Young
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제18권2호
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    • pp.181-192
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    • 2014
  • In this paper, we propose a robust real-time myocardial border tracking algorithm for echocardiography. Commonly, after an initial contour of LV border is traced at one or two frame from the entire cardiac cycle, LV contour tracking is performed over the remaining frames. Among a variety of tracking techniques, optical flow method is the most widely used for motion estimation of moving objects. However, when echocardiography data is heavily corrupted in some local regions, the errors bring the tracking point out of the endocardial border, resulting in distorted LV contours. This shape distortion often occurs in practice since the data acquisition is affected by ultrasound artifacts, dropout or shadowing phenomena of cardiac walls. The proposed method deals with this shape distortion problem and reflects the motion realistic LV shape by applying global deformation modeled as affine transform partitively to the contour. We partition the tracking points on the contour into a few groups and determine each affine transform governing the motion of the partitioned contour points. To compute the coefficients of each affine transform, we use the least squares method with equality constraints that are given by the relationship between the coefficients and a few contour points showing good tracking results. Many real experiments show that the proposed method supports better performance than existing methods.

합성곱 신경망을 통한 강건한 온라인 객체 추적 (Robust Online Object Tracking via Convolutional Neural Network)

  • 길종인;김만배
    • 방송공학회논문지
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    • 제23권2호
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    • pp.186-196
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    • 2018
  • 본 논문에서는 객체를 추적하기 위해 합성곱 신경망 모델을 이용한 온라인 추적 기법을 제안한다. 오프라인에 모델을 학습시키기 위해서는 많은 수의 훈련 샘플이 필요하다. 이러한 문제를 해결하기 위해, 학습되지 않은 모델을 사용하고, 실험 영상으로부터 직접 훈련 샘플을 수집하여 모델을 갱신한다. 기존의 방법들은 많은 훈련 샘플을 획득하여 모델의 학습에 사용하였지만, 본 논문에서는 적은 수의 훈련 샘플만으로도 객체의 추적이 가능함을 증명한다. 또한 컬러 정보를 활용하여 새로운 손실 함수를 정의하였고 이로부터 잘못 수집된 훈련 샘플로 인해 모델이 잘못된 방향으로 학습되는 문제를 방지한다. 실험을 통해 4가지 비교 방법과 동등하거나 개선된 추적 성능을 보임을 증명하였다.

Robust Adaptive Wavelet-Neural-Network Sliding-Mode Speed Control for a DSP-Based PMSM Drive System

  • El-Sousy, Fayez F.M.
    • Journal of Power Electronics
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    • 제10권5호
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    • pp.505-517
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    • 2010
  • In this paper, an intelligent sliding-mode speed controller for achieving favorable decoupling control and high precision speed tracking performance of permanent-magnet synchronous motor (PMSM) drives is proposed. The intelligent controller consists of a sliding-mode controller (SMC) in the speed feed-back loop in addition to an on-line trained wavelet-neural-network controller (WNNC) connected in parallel with the SMC to construct a robust wavelet-neural-network controller (RWNNC). The RWNNC combines the merits of a SMC with the robust characteristics and a WNNC, which combines artificial neural networks for their online learning ability and wavelet decomposition for its identification ability. Theoretical analyses of both SMC and WNNC speed controllers are developed. The WNN is utilized to predict the uncertain system dynamics to relax the requirement of uncertainty bound in the design of a SMC. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding mode speed controller. An experimental system is established to verify the effectiveness of the proposed control system. All of the control algorithms are implemented on a TMS320C31 DSP-based control computer. The simulated and experimental results confirm that the proposed RWNNC grants robust performance and precise response regardless of load disturbances and PMSM parameter uncertainties.