• Title/Summary/Keyword: recursive system

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Development of an Automatic Noise Detection System for Factory Automation (공장자동화를 위한 소음 자동검사 시스템의 개발에 관한 연구)

  • Yoon, Kang-Sup;Kim, Hyun-Gi;Lee, Man-Hyung;Lee, Kwon-Soon
    • Journal of the Korean Society for Precision Engineering
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    • v.9 no.2
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    • pp.128-137
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    • 1992
  • An automatic noise detection system is developed to sense abnormal noises in operating a microwave electronic range. A noise detection method is presented which accounts for the effects of backgound and dynamic noises of the range. A recursive formula used as a noise estimator is a special case of the discrete-time Kalman filter in stochastic processes. Noise levels were measured using a noise acquisition processor in a closed room free of background noise, and detected signals were processes using a microcomputer. The results obtaines showed that the fault detection system should be fast in response to the data acquired and should be high in accuracy and reliability.

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An Adaptive Multiple Target Tracking Filter Using the EM Algorithm (EM 알고리즘을 이용한 적응다중표적추적필터)

  • Hong Jeong;Park, Jeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.5
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    • pp.583-597
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    • 2001
  • Tracking the targets of interest has been one of the major research areas in radar surveillance system. We formulate the tracking problem as an incomplete data problem and apply the EM algorithm to obtain the MAP estimate. The resulting filter has a recursive structure analogous to the Kalman filter. The difference is that the measurement-update deals with multiple measurements and the parameter-update can estimate the system parameters. Through extensive experiments, it turns out that the proposed system is better than PDAF and NNF in tracking the targets. Also, the performance degrades gracefully as the disturbances become stronger.

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Time Variant Parameter Estimation using RLS Algorithm with Adaptive Forgetting Factor Based on Newton-Raphson Method (Newton-Raphson법 기반의 적응 망각율을 갖는 RLS 알고리즘에 의한 원격센서시스템의 시변파라메타 추정)

  • Kim, Kyung-Yup;Lee, Joon-Tark
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.04a
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    • pp.435-439
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    • 2007
  • This paper deals with RLS algorithm using Newton-Raphson method based adaptive forgetting factor for a passive telemetry RF sensor system in order to estimate the time variant parameter to be included in RF sensor model. For this estimation with RLS algorithm, phasor typed RF sensor system modelled with inductive coupling principle is used. Instead of applying constant forgetting factor to estimate time variant parameter, the adaptive forgetting factor based on Newton-Raphson method is applied to RLS algorithm without constant forgetting factor to be determined intuitively. Finally, we provide numerical examples to evaluate the feasibility and generality of the proposed method in this paper.

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Backstepping Control and Synchronization for 4-D Lorenz-Stenflo Chaotic System with Single Input

  • Yu, Sung-Hun;Hyun, Chang-Ho;Park, Mig-Non
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.11 no.3
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    • pp.143-148
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    • 2011
  • In this paper, a backstepping design is proposed to achieve stabilization and synchronization for the Lorenz-Stenflo (LS) chaotic system. The proposed method is a recursive Lyapunov-based scheme and provides a systematic procedure to design stabilizing controllers. The proposed controller enables stabilization of the chaotic motion and synchronization of two identical LS chaotic systems using only a single control input. Numerical simulations are presented to validate the proposed method.

The Concatenated Coding Scheme for OFDM system over burst noise channel

  • Byung-Hyun, Moon;Sang-Min, Choi
    • Journal of Korea Society of Industrial Information Systems
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    • v.9 no.2
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    • pp.17-22
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    • 2004
  • In this paper, a concatenated RS and Turbo code is proposed for OFDM system over burst error channel. The concatenated code used in this study is a RS(255,202) code and a rate 1/2 turbo code. The turbo code uses 2 recursive systematic convolutional (RSC) code as the constituent codes and the parity bit are punctured to get the desired code rate. It is shown by simulation that the conventional OFDM system fails when there exists burst noise. The concatenated RS and turbo code obtains at least 5dB gain over the turbo code at the bit error probability of 10/sup -3/.

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Resolution Improvement of Ultrasound Signal Using Kalman Filter (칼만 필터를 이용한 초음파 신호의 해상력 향상)

  • Woo, Kwang-B.;Nam, Sang-E.;Shin, Dong-H.;Chin, Young-M.;Lee, Sung-M.
    • Proceedings of the KOSOMBE Conference
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    • v.1985 no.06
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    • pp.15-19
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    • 1985
  • This study deals with a kind of signal processing, Kalman filtering techniques, which are applied to ultrasound signal to improve resolution capability. The main advantage of Kalman filter algorithm for the analysis of reflected ultrasound signal is its recursive structure which can be easily adapted to time-varing system. In state-space description of the system, the 6th order system produces the best spectral approximation to the source pulse. As a result of spectrum analysis, 6th order estimator for two closely spaced (0.5mm) reflectors enhance resolution by 4dB - 10dB. By using this result, the possibility to detect even minute tumor is found.

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Input Constrained Receding Horizon Control with Nonzero Set Points and Model Uncertainties

  • Lee, Young-Il
    • Transactions on Control, Automation and Systems Engineering
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    • v.3 no.3
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    • pp.159-163
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    • 2001
  • An input constrained receding horizon predictive control algorithm for uncertain systems with nonzero set points is proposed. for constant nonzero set points, models with uncertainty can be converted into an augmented incremental system through the use of integrators and the problem is transformed into a zero-state regulation problem for the incremental system. But the original constraints on inputs are converted into constraints on the sum of control inputs at each time instants, which have not been dealt in earlier constrained robust receding horizon control problems. Recursive state bounding technique and worst case minimizing strategy developed in earlier works are applied to the augmented incremental system to yield an offset error free controller. The resulting algorithm is formulated so that it can be solved using LP.

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Robust Nonlinear H$\infty$ FIR Filtering for Time-Varying Systems

  • Ryu, Hee-Seob;Son, Won-Kee;Kwon, Oh-Kyu
    • Transactions on Control, Automation and Systems Engineering
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    • v.2 no.3
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    • pp.175-181
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    • 2000
  • This paper investigates the robust nonlinear H$_{\infty}$ filter with FIR(Finite Impulse Response) structure for nonlinear discrete time-varying uncertain systems represented by the state-space model having parameter uncertainty. Firstly, when there is no parameter uncertainty in the system, the discrete-time nominal nonlinear H$_{\infty}$ FIR filter is derived by using the equivalence relationship between the FIR filter and the recursive filter, which corresponds to the standard nonlinear H$_{\infty}$ filter. Secondly, when the system has the parameter uncertainty, the robust nonlinear H$_{\infty}$ FIR filter is proposed for the discrete-time nonlinear uncertain systems.

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Self-Tuning Position Control of a Remotely Operated Vehicle (원격무인 잠수정의 자기동조 위치제어)

  • Lee, Pan-Muk
    • Journal of Ocean Engineering and Technology
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    • v.3 no.2
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    • pp.551-551
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    • 1989
  • In general, a remotely operated vehicle(ROV) operates at deep sea. The control system of ROV is composed of two local loops; the first loop placed on the surface vessel monitors and manipulates the attitude of the ROV using joystick, and the second part on the ROV automatically controls thrusters and acquires positional data. This paper presents a position control simulation of a ROV using an adaptive controller and discusses the control effects of two different conditions. The design of an adaptive control system is obtained by the application of a self-tuning controller with the minimization of an appropriate cost function. The parameters of the control system are estimated by a recursive least square method(RLS). In the simulation, a Runge-Kutta method is used for the numerical integration and the generated outputs are obtained by adding measurement errors. Additionally, this paper discusses the mathematical modelling of a ROV and make a survey of control systems.

Self-Tuning Position Control of a Remotely Operated Vehicle (원격무인 잠수정의 자기동조 위치제어)

  • Lee, Pan-Muk
    • Journal of Ocean Engineering and Technology
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    • v.3 no.2
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    • pp.51-58
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    • 1989
  • In general, a remotely operated vehicle(ROV) operates at deep sea. The control system of ROV is composed of two local loops; the first loop placed on the surface vessel monitors and manipulates the attitude of the ROV using joystick, and the second part on the ROV automatically controls thrusters and acquires positional data. This paper presents a position control simulation of a ROV using an adaptive controller and discusses the control effects of two different conditions. The design of an adaptive control system is obtained by the application of a self-tuning controller with the minimization of an appropriate cost function. The parameters of the control system are estimated by a recursive least square method(RLS). In the simulation, a Runge-Kutta method is used for the numerical integration and the generated outputs are obtained by adding measurement errors. Additionally, this paper discusses the mathematical modelling of a ROV and make a survey of control systems.

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