• 제목/요약/키워드: Linear Discrete-Time Systems

검색결과 319건 처리시간 0.04초

로봇 매니퓰레이터에 대한 비례.적분.미분 조절기 설계 (PID regulator design for robot manipulators)

  • 남헌성;김천중;유준
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
    • /
    • pp.647-651
    • /
    • 1992
  • This paper presents a model-based control scheme for a robot manipulator to track a desired trajectory as closely as possible in spite of a wide range of manipulator motions and parameter uncertainties of links and payload. The scheme has two components: a nominal control and a variational control. The nominal control, generated from direct calculation of the manipulator dynamics along a desired trajectory, drives the manipulator to a neighborhood of the trajectory. Then a discrete-time PID regulator is designed based on the linearized dynamic model and Linear Quadratic(LQ) method, which generates the variational control that regulates perturbations in the vicinity of the desired trajectory.

  • PDF

잡음하에서의 적응관측자 및 적응식별기에 관한 연구 (A Study on the Adaptive Observer/Adaptive Identifier in the Presence of Noise)

  • 최종호;남석우
    • 대한전기학회논문지
    • /
    • 제39권1호
    • /
    • pp.83-91
    • /
    • 1990
  • An adaptive observer which is applicable to discrete linear time invariant systems of ARMA type in the presence of noise is proposed. It first estimates the system parameters of the MA type by applying only the system input to the observer. Then it estimates the output which corresponds to the output of the system without any noise. This is a special case of Suzuki's adaptive observer. This estimated output is applied to Suzuki's adaptive observer to estimate the system parameters of ARMA type and the states. The proposed method can make the estimate errors of the system parameters sufficiently small even in the presence of noise in the system. It can also make the estimate errors of the states of the system sufficiently small when there is no process noise. These properties of the proposed adaptive observer is certified by computer simulation.

  • PDF

Decentralized Moving Average Filtering with Uncertainties

  • Song, Il Young
    • 센서학회지
    • /
    • 제25권6호
    • /
    • pp.418-422
    • /
    • 2016
  • A filtering algorithm based on the decentralized moving average Kalman filter with uncertainties is proposed in this paper. The proposed filtering algorithm presented combines the Kalman filter with the moving average strategy. A decentralized fusion algorithm with the weighted sum structure is applied to the local moving average Kalman filters (LMAKFs) of different window lengths. The proposed algorithm has a parallel structure and allows parallel processing of observations. Hence, it is more reliable than the centralized algorithm when some sensors become faulty. Moreover, the choice of the moving average strategy makes the proposed algorithm robust against linear discrete-time dynamic model uncertainties. The derivation of the error cross-covariances between the LMAKFs is the key idea of studied. The application of the proposed decentralized fusion filter to dynamic systems within a multisensor environment demonstrates its high accuracy and computational efficiency.

멀티레이트 샘플치 시스템: 최적 디지털 재설계 기법 (Multirate Sampled-Data Control System: Optimal Digital Redesign Approach)

  • 김도완;박진배;장권규;추영훈
    • 대한전기학회:학술대회논문집
    • /
    • 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
    • /
    • pp.708-710
    • /
    • 2004
  • This paper studies a multirate sampled-data control for LTI systems by using the digital redesign (DR) method. In this note, to well tackle the problem associated with both the state matching and the stabilization, our nobel strategy is to minimize the linear quadratic cost function. The main features of the proposed method are that i) the delta-operator-based descretization method is applied to improve the state-matching performance in the fast sampling limit and/or the large input multiplicity; ii) the proposed multirate control scheme can improve the state-matching performance in the long sampling limit; iii) some sufficient conditions that guarantee the stability of the closed-loop discrete-time system and provide a guarantee cost for the cost function can be formulated in the LMIs format; and iv) an optimal sampled-data controller in the sense of minimizing the upper bound of the cost function is also given by means of an LMI optimization procedure.

  • PDF

마이크로폰 31개로 이루어진 선형배열 음향렌즈의 구성과 실험 (Development and Experiment of a Linear Array Acoustic Lens with 31 Microphones)

  • 현석봉;민동현;김수용
    • 한국음향학회지
    • /
    • 제13권5호
    • /
    • pp.15-23
    • /
    • 1994
  • 31개의 마이크로폰이 34mm 간격으로 선형배열된 음향영상장치용 전자 렌즈를 제작하였다. 마이크로폰을 이용한 음향센서의 공진주파수는 20kHz이고, 16개의 마이크로폰은 수평으로 나머지 15개의 마이크로폰은 수직으로 배치되어 있어서, 음원의 2차원적인 각도를 알아낼 수 있고 음원의 운동을 실시간으로 추적할 수 있다. 이산 푸리어변환할때 ㅈ나타나는 aliasing 문제 때문에 제작된 렌즈의 최대 관찰가능각도는 15도로 제한된다. 또한 촛점을 맞추기 위해 직각위상 검파방법을 이용하였다. 무향실에서 PC를 이용하여 음향렌즈를 실험하였으며 음향영상이론과 일치하는 결과를 얻었다.

  • PDF

On discrete nonlinear self-tuning control

  • Mohler, R.-R.;Rajkumar, V.;Zakrzewski, R.-R.
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
    • /
    • pp.1659-1663
    • /
    • 1991
  • A new control design methodology is presented here which is based on a nonlinear time-series reference model. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible a.c. transmission system (FACTS) with series capacitor power feedback control is studied. A bilinear auto-regressive moving average (BARMA) reference model is identified from system data and the feedback control manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index (J). A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack. These applications are typical of the numerous plants for which nonlinear adaptive control has the potential to provide significant performance improvements. For aircraft control, significant maneuverability gains can provide safer transportation under large windshear disturbances as well as tactical advantages. For FACTS, there is the potential for significant increase in admissible electric power transmission over available transmission lines along with energy conservation. Electric power systems are inherently nonlinear for significant transient variations from synchronism such as may result for large fault disturbances. In such cases, traditional linear controllers may not stabilize the swing (in rotor angle) without inefficient energy wasting strategies to shed loads, etc. Fortunately, the advent of power electronics (e.g., high-speed thyristors) admits the possibility of adaptive control by means of FACTS. Line admittance manipulation seems to be an effective means to achieve stabilization and high efficiency for such FACTS. This results in parametric (or multiplicative) control of a highly nonlinear plant.

  • PDF

센서 데이터의 시계열 특성을 고려한 딥러닝 모델 기반의 공압 실린더 고장 감지 시스템 구현 (Real-time Fault Detection System of a Pneumatic Cylinder Via Deep-learning Model Considering Time-variant Characteristic of Sensor Data)

  • 김병수;송근명;이민정;백수정
    • 산업경영시스템학회지
    • /
    • 제47권2호
    • /
    • pp.10-20
    • /
    • 2024
  • In recent automated manufacturing systems, compressed air-based pneumatic cylinders have been widely used for basic perpetration including picking up and moving a target object. They are relatively categorized as small machines, but many linear or rotary cylinders play an important role in discrete manufacturing systems. Therefore, sudden operation stop or interruption due to a fault occurrence in pneumatic cylinders leads to a decrease in repair costs and production and even threatens the safety of workers. In this regard, this study proposed a fault detection technique by developing a time-variant deep learning model from multivariate sensor data analysis for estimating a current health state as four levels. In addition, it aims to establish a real-time fault detection system that allows workers to immediately identify and manage the cylinder's status in either an actual shop floor or a remote management situation. To validate and verify the performance of the proposed system, we collected multivariate sensor signals from a rotary cylinder and it was successful in detecting the health state of the pneumatic cylinder with four severity levels. Furthermore, the optimal sensor location and signal type were analyzed through statistical inferences.

Optimum time history analysis of SDOF structures using free scale of Haar wavelet

  • Mahdavi, S.H.;Shojaee, S.
    • Structural Engineering and Mechanics
    • /
    • 제45권1호
    • /
    • pp.95-110
    • /
    • 2013
  • In the recent decade, practical of wavelet technique is being utilized in various domain of science. Particularly, engineers are interested to the wavelet solution method in the time series analysis. Fundamentally, seismic responses of structures against time history loading such as an earthquake, illustrates optimum capability of systems. In this paper, a procedure using particularly discrete Haar wavelet basis functions is introduced, to solve dynamic equation of motion. In the proposed approach, a straightforward formulation in a fluent manner is derived from the approximation of the displacements. For this purpose, Haar operational matrix is derived and applied in the dynamic analysis. It's free-scaled matrix converts differential equation of motion to the algebraic equations. It is shown that accuracy of dynamic responses relies on, access of load in the first step, before piecewise analysis added to the technique of equation solver in the last step for large scale of wavelet. To demonstrate the effectiveness of this scheme, improved formulations are extended to the linear and nonlinear structural dynamic analysis. The validity and effectiveness of the developed method is verified with three examples. The results were compared with those from the numerical methods such as Duhamel integration, Runge-Kutta and Wilson-${\theta}$ method.

Complexity Estimation Based Work Load Balancing for a Parallel Lidar Waveform Decomposition Algorithm

  • Jung, Jin-Ha;Crawford, Melba M.;Lee, Sang-Hoon
    • 대한원격탐사학회지
    • /
    • 제25권6호
    • /
    • pp.547-557
    • /
    • 2009
  • LIDAR (LIght Detection And Ranging) is an active remote sensing technology which provides 3D coordinates of the Earth's surface by performing range measurements from the sensor. Early small footprint LIDAR systems recorded multiple discrete returns from the back-scattered energy. Recent advances in LIDAR hardware now make it possible to record full digital waveforms of the returned energy. LIDAR waveform decomposition involves separating the return waveform into a mixture of components which are then used to characterize the original data. The most common statistical mixture model used for this process is the Gaussian mixture. Waveform decomposition plays an important role in LIDAR waveform processing, since the resulting components are expected to represent reflection surfaces within waveform footprints. Hence the decomposition results ultimately affect the interpretation of LIDAR waveform data. Computational requirements in the waveform decomposition process result from two factors; (1) estimation of the number of components in a mixture and the resulting parameter estimates, which are inter-related and cannot be solved separately, and (2) parameter optimization does not have a closed form solution, and thus needs to be solved iteratively. The current state-of-the-art airborne LIDAR system acquires more than 50,000 waveforms per second, so decomposing the enormous number of waveforms is challenging using traditional single processor architecture. To tackle this issue, four parallel LIDAR waveform decomposition algorithms with different work load balancing schemes - (1) no weighting, (2) a decomposition results-based linear weighting, (3) a decomposition results-based squared weighting, and (4) a decomposition time-based linear weighting - were developed and tested with varying number of processors (8-256). The results were compared in terms of efficiency. Overall, the decomposition time-based linear weighting work load balancing approach yielded the best performance among four approaches.

분산 제약을 갖는 비선형 시스템의 최적 퍼지 필터 (Optimal Fuzzy Filter for Nonlinear Systems with Variance Constraints)

  • 노선영;박진배;주영훈
    • 한국지능시스템학회논문지
    • /
    • 제22권5호
    • /
    • pp.549-554
    • /
    • 2012
  • 본 논문에서는 추정 분산 제약을 갖는 비선형 이산시간에 대한 최적의 퍼지 필터에 대한 내용을 다루고자 한다. 필터를 설계할 때, 추정오차의 분산값은 필터의 성능이 결정하는 변수중 하나다. 이런 분산값에 더욱 강인한 필터를 설계하고자, 분산 제약 조건을 주어 필터를 설계하고자 한다. 먼저, 비선형 모델을 Tagaki-Sugeno 퍼지 모델을 이용하여 선형 모델로 변형한 후, 이 모델을 기반으로 선형 필터를 디자인한다. 이때 필터설계 과정 중 필터의 각 파라미터값을 구하기 위해 상태 추정오차 값은 평균제곱에 제한되며, 상태오차의 정상상태 분산값은 각각의 미리 정한 상한 제한 값 보다 작은 조건에서 필터를 설계하여 선형행렬부등식과 대수 이차 행렬부등식을 이용하여 파라미터값을 구한다. 이렇게 설계된 퍼지 필터는 트럭트레일러 시뮬레이션을 통해 설계 과정과 성능을 보여준다.