• Title, Summary, Keyword: linear time-varying system

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Kalman Randomized Joint UKF Algorithm for Dual Estimation of States and Parameters in a Nonlinear System

  • Safarinejadian, Behrouz;Vafamand, Navid
    • Journal of Electrical Engineering and Technology
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    • v.10 no.3
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    • pp.1212-1220
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    • 2015
  • This article presents a new nonlinear joint (state and parameter) estimation algorithm based on fusion of Kalman filter and randomized unscented Kalman filter (UKF), called Kalman randomized joint UKF (KR-JUKF). It is assumed that the measurement equation is linear. The KRJUKF is suitable for time varying and severe nonlinear dynamics and does not have any systematic error. Finally, joint-EKF, dual-EKF, joint-UKF and KR-JUKF are applied to a CSTR with cooling jacket, in which production of propylene glycol happens and performance of KR-JUKF is evaluated.

Optimal Array Design of the Permanent Magnet in an Eddy Current Brake (와전류 브레이크의 영구자석배열 최적설계)

  • Choi, Jae-Seok;Yoo, Jeong-Hoon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.33 no.7
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    • pp.658-663
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    • 2009
  • Eddy current is usually generated in the material with high conductivity by time-varying source such as AC current and also is induced by the moving source with relative velocity. The contactless magnetic brake makes use of the braking force from the eddy current generated by the moving source and currently used for the secondary brakes of heavy trucks, buses and rail vehicles. This study aims to design the magnetization pattern of the eddy current brake system of a permanent magnet type where the design aim is to maximize the braking force. The analysis of brake systems is based on the two-dimensional finite element analysis. We use the sequential linear programming as the optimizer and the adjoint variable method is applied for the sensitivity analysis.

Delay-range-dependent Stability Analysis and Stabilization for Nonlinear Systems : T-S Fuzzy Model Approach (비선형 시스템의 시간 지연 간격에 종속적인 안정도 분석 및 제어기 설계: TS 퍼지 모델 적용)

  • Song, Min-Kook;Park, Jin-Bae;Kim, Jin-Kyu;Joo, Young-Hoon
    • Journal of Korean Institute of Intelligent Systems
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    • v.19 no.3
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    • pp.337-342
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    • 2009
  • This paper concerns delay-range-dependent robust stability and stabilization for time-delay nonliner system via T-S fuzzy model approach. The time delay is assumed to be a time-varying continuous function belonging to a given range. On the basis of a novel Lyapunov-Krasovskii functional, which includes the information of the range, delay-range-dependent stability criteria are established in terms of linear matrix inequality. It is shown that the new criteria can provide less conservative results than some existing ones. Moreover, the stability criteria are also used to design the stabilizing state-feedback controllers. Numerical examples are given to demonstrate the applicability of the proposed approach.

The Prediction and Analysis of the Power Energy Time Series by Using the Elman Recurrent Neural Network (엘만 순환 신경망을 사용한 전력 에너지 시계열의 예측 및 분석)

  • Lee, Chang-Yong;Kim, Jinho
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.41 no.1
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    • pp.84-93
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    • 2018
  • In this paper, we propose an Elman recurrent neural network to predict and analyze a time series of power energy consumption. To this end, we consider the volatility of the time series and apply the sample variance and the detrended fluctuation analyses to the volatilities. We demonstrate that there exists a correlation in the time series of the volatilities, which suggests that the power consumption time series contain a non-negligible amount of the non-linear correlation. Based on this finding, we adopt the Elman recurrent neural network as the model for the prediction of the power consumption. As the simplest form of the recurrent network, the Elman network is designed to learn sequential or time-varying pattern and could predict learned series of values. The Elman network has a layer of "context units" in addition to a standard feedforward network. By adjusting two parameters in the model and performing the cross validation, we demonstrated that the proposed model predicts the power consumption with the relative errors and the average errors in the range of 2%~5% and 3kWh~8kWh, respectively. To further confirm the experimental results, we performed two types of the cross validations designed for the time series data. We also support the validity of the model by analyzing the multi-step forecasting. We found that the prediction errors tend to be saturated although they increase as the prediction time step increases. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric and the gas energies.

Optimal Temperature Tracking Control of a Polymerization Batch Reactor by Adaptive Input-Output Linearization

  • Noh, Kap-Kyun;Dongil Shin;Yoon, En-Sup;Rhee, Hyun-Ku
    • Transactions on Control, Automation and Systems Engineering
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    • v.4 no.1
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    • pp.62-74
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    • 2002
  • The tracking of a reference temperature trajectory in a polymerization batch reactor is a common problem and has critical importance because the quality control of a batch reactor is usually achieved by implementing the trajectory precisely. In this study, only energy balances around a reactor are considered as a design model for control synthesis, and material balances describing concentration variations of involved components are treated as unknown disturbances, of which the effects appear as time-varying parameters in the design model. For the synthesis of a tracking controller, a method combining the input-output linearization of a time-variant system with the parameter estimation is proposed. The parameter estimation method provides parameter estimates such that the estimated outputs asymptotically follow the measured outputs in a specified way. Since other unknown external disturbances or uncertainties can be lumped into existing parameters or considered as another separate parameters, the method is useful in practices exposed to diverse uncertainties and disturbances, and the designed controller becomes robust. And the design procedure and setting of tuning parameters are simple and clear due to the resulted linear design equations. The performances and the effectiveness of the proposed method are demonstrated via simulation studies.

A Finite Impulse Response Fixed-lag Smoother for Discrete-time Nonlinear Systems (이산 비선형 시스템에 대한 유한 임펄스 응답 고정 시간 지연 평활기)

  • Kwon, Bo-Kyu;Han, Sekyung;Han, Soohee
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.9
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    • pp.807-810
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    • 2015
  • In this paper, a finite impulse response(FIR) fixed-lag smoother is proposed for discrete-time nonlinear systems. If the actual state trajectory is sufficiently close to the nominal state trajectory, the nonlinear system model can be divided into two parts: The error-state model and the nominal model. The error state can be estimated by adapting the optimal time-varying FIR smoother to the error-state model, and the nominal state can be obtained directly from the nominal trajectory model. Moreover, in order to obtain more robust estimates, the linearization errors are considered as a linear function of the estimation errors. Since the proposed estimator has an FIR structure, the proposed smoother can be expected to have better estimation performance than the IIR-structured estimators in terms of robustness and fast convergence. Additionally the proposed method can give a more general solution than the optimal FIR filtering approach, since the optimal FIR smoother is reduced to the optimal FIR filter by setting the fixed-lag size as zero. To illustrate the performance of the proposed method, simulation results are presented by comparing the method with an optimal FIR filtering approach and linearized Kalman filter.

A Study on the Underwater Navigation System with Adaptive Receding Horizon Kalman Filter (적응 이동 구간 칼만 필터를 이용한 무인 잠수정의 항법 시스템에 관한 연구)

  • Jo, Gyung-Nam;Seo, Dong-C.;Choi, Hang-S.
    • Journal of the Society of Naval Architects of Korea
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    • v.45 no.3
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    • pp.269-279
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    • 2008
  • In this paper, an underwater navigation system with adaptive receding horizon Kalman filter (ARHKF) is studied. It is well known that incorrect statistical information and temporal disturbance invoke errors of any navigation systems with Kalman filter, which makes the autonomous navigation difficult in real underwater environment. In this context, two kinds of problems are herein considered. The first one is the development of an algorithm, which estimates the noise covariance of a linear discrete time-varying stochastic system. The second one is the implementation of ARHKF to underwater navigation systems. The performance of the derived estimation algorithm of noise covariance and the ARHKF are verified by simulation and experiment in the towing tank of Seoul National University.

Traffic Signal Control Algorithm for Isolated Intersections Based on Travel Time (독립교차로의 통행시간 기반 신호제어 알고리즘)

  • Jeong, Youngje;Park, Sang Sup;Kim, Youngchan
    • Journal of Korean Society of Transportation
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    • v.30 no.6
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    • pp.71-80
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    • 2012
  • This research suggested a real-time traffic signal control algorithm using individual vehicle travel times on an isolated signal intersection. To collect IDs and passing times from individual vehicles, space-based surveillance systems such as DSRC were adopted. This research developed models to estimate arrival flow rates, delays, and the change rate in delay, by using individual vehicle's travel time data. This real-time signal control algorithm could determine optimal traffic signal timings that minimize intersection delay, based on a linear programming. A micro simulation analysis using CORSIM and RUN TIME EXTENSION verified saturated intersection conditions, and determined the optimal traffic signal timings that minimize intersection delay. In addition, the performance of algorithm varying according to market penetration was examined. In spite of limited results from a specific scenario, this algorithm turned out to be effective as long as the probe rate exceeds 40 percent. Recently, space-based traffic surveillance systems are being installed by various projects, such as Hi-pass, Advanced Transportation Management System (ATMS) and Urban Transportation Information System (UTIS) in Korea. This research has an important significance in that the propose algorithm is a new methodology that accepts the space-based traffic surveillance system in real-time signal operations.

Linear Quadratic Controller Design of Insect-Mimicking Flapping Micro Aerial Vehicle (곤충모방 날갯짓 비행체의 LQ 제어기 설계)

  • Kim, Sungkeun;Kim, Inrae;Kim, Seungkeun;Suk, Jinyoung
    • The Journal of Advanced Navigation Technology
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    • v.21 no.5
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    • pp.450-458
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    • 2017
  • This paper presents dynamic modelling and simulation study on attitude/altitude control of an insect-mimicking flapping micro aerial vehicle during hovering. Mathematical modelling consists of three parts: simplified flapping kinematics, flapping-wing aerodynamics, and six degree of freedom dynamics. Attitude stabilization is accomplished through linear quadratic regulator based on the linearized model of the time-varying nonlinear system, and altitude control is designed in the outer loop using PID control. The performance of the proposed controller is verified through numerical simulation where attitude stabilization and altitude control is done for hovering. In addition, it is confirmed that the attitude channel by periodic control is marginally stable against periodic pitching moment caused by flapping.

Head tracking system using image processing (영상처리를 이용한 머리의 움직임 추적 시스템)

  • 박경수;임창주;반영환;장필식
    • Journal of the Ergonomics Society of Korea
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    • v.16 no.3
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    • pp.1-10
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    • 1997
  • This paper is concerned with the development and evaluation of the camera calibration method for a real-time head tracking system. Tracking of head movements is important in the design of an eye-controlled human/computer interface and the area of virtual environment. We proposed a video-based head tracking system. A camera was mounted on the subject's head and it took the front view containing eight 3-dimensional reference points(passive retr0-reflecting markers) fixed at the known position(computer monitor). The reference points were captured by image processing board. These points were used to calculate the position (3-dimensional) and orientation of the camera. A suitable camera calibration method for providing accurate extrinsic camera parameters was proposed. The method has three steps. In the first step, the image center was calibrated using the method of varying focal length. In the second step, the focal length and the scale factor were calibrated from the Direct Linear Transformation (DLT) matrix obtained from the known position and orientation of the camera. In the third step, the position and orientation of the camera was calculated from the DLT matrix, using the calibrated intrinsic camera parameters. Experimental results showed that the average error of camera positions (3- dimensional) is about $0.53^{\circ}C$, the angular errors of camera orientations are less than $0.55^{\circ}C$and the data aquisition rate is about 10Hz. The results of this study can be applied to the tracking of head movements related to the eye-controlled human/computer interface and the virtual environment.

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