• 제목/요약/키워드: Recursive estimation

검색결과 330건 처리시간 0.031초

이산 적응 관측자를 이용한 유도전동기의 회전자 속도 추정 (Induction motor rotor speed estimation using discrete adaptive observer)

  • 이상철;최창호;남광희
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.1060-1062
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    • 1996
  • This paper presents a discrete adaptive observer for MIMO system of an IM model in DQ reference model. The IM model in the stationary frame is discretized and it is transformed into the canonical observer form. The unknown parameter is choosen as rotor speed. The adaptive law for parameter adjustment is obtained as a set of recursive equations which are derived by utilizing an exponentially weighted normalized least-square method. The proposed adaptive observer converges rapidly and is also shown to track time-varying plant parameter quickly. Its effectiveness has been demonstrated by computer simulation.

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계수 추정 기법을 이용한 동조자이로스코프 온도 제어기의 설계 (Design of the Temperature Controller for a Dynamically Tuned Gyroscope Using Parameter Estimation Methods)

  • 송진우;이장규;강태삼;김진원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.1146-1148
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    • 1996
  • In this paper, uncertain parameters of the heat transfer model of a Dynamically Tuned Gyroscope (DTG) are estimated by the Recursive Least Squares (RLS) method. Also, using this model, a temperature controller for a DTG is designed. As the temperature controller, a PI controller is used. It is presented that a controller can be easily designed when the heat transfer model of a DTG is used. By simulations and experiments, it is shown that the estimated heat transfer model is appropriate and the desired performance of the temperature controller is satisfied.

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EM 알고리즘을 통한 칼만 필터의 성능 개선 (Improved Kalman filter performance via EM algorithm)

  • 강지혜;김성수
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 D
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    • pp.2615-2617
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    • 2003
  • The Kalman filter is a recursive Linear Estimator for the linear dynamic systems(LDS) affected by two different noises called process noise and measurement noise both of which are uncorrelated white. The Expectation Maximization(EM) algorithm is employed in this paper as a preprocessor to reinforce the effectiveness of Kalman estimator. Particularly, we focus on the relation between Kalman filter and EM algorithm in the LDS. In this paper, we propose a new algorithm to improve the performance on the parameter estimation via EM algorithm, which improves the overall process of Kalman filtering. Since Kalman filter algorithm not only needs the system parameters but also is very sensitive the initial state conditions, the initial conditions decided through EM turns out to be very effective. In experiments, the computer simulation results ate provided to demonstrate the superiority of the proposed algorithm.

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재귀최소자승법을 이용한 수퍼커패시터 뱅크의 커패시턴스 실시간 추정방법 (Online Capacitance Estimation of Supercapacitor Bank Using Recursive Least Square Method)

  • 조성우;신규범;조현식;차한주
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2015년도 전력전자학술대회 논문집
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    • pp.449-450
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    • 2015
  • 본 논문에서는 재귀최소자승법을 이용한 수퍼커패시터 뱅크의 실시간 커패시턴스 추정방법에 대해 서술하였으며, 커패시터의 수명은 초기용량에서 약 25%가 감소한 경우 수명을 다했다고 판단한다. 수명을 다한 커패시터를 사용할 경우 시스템의 성능과 안전을 보장할 수 없으므로 커패시터를 교체할 적절한 시기를 판단하는 것은 매우 중요하다. 따라서 본 논문에서는 재귀최소자승법으로 수퍼커패시터 뱅크의 커패시턴스를 측정할 수 있는 방법을 제안하였고, 이를 시뮬레이션을 통해 타당성을 검증하였다.

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A generalized regime-switching integer-valued GARCH(1, 1) model and its volatility forecasting

  • Lee, Jiyoung;Hwang, Eunju
    • Communications for Statistical Applications and Methods
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    • 제25권1호
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    • pp.29-42
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    • 2018
  • We combine the integer-valued GARCH(1, 1) model with a generalized regime-switching model to propose a dynamic count time series model. Our model adopts Markov-chains with time-varying dependent transition probabilities to model dynamic count time series called the generalized regime-switching integer-valued GARCH(1, 1) (GRS-INGARCH(1, 1)) models. We derive a recursive formula of the conditional probability of the regime in the Markov-chain given the past information, in terms of transition probabilities of the Markov-chain and the Poisson parameters of the INGARCH(1, 1) process. In addition, we also study the forecasting of the Poisson parameter as well as the cumulative impulse response function of the model, which is a measure for the persistence of volatility. A Monte-Carlo simulation is conducted to see the performances of volatility forecasting and behaviors of cumulative impulse response coefficients as well as conditional maximum likelihood estimation; consequently, a real data application is given.

Adaptive control of gas metal arc welding process

  • Song, Jae-Bok;Hardt, David-E.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.191-196
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    • 1993
  • Since the welding process is complex and highly nonlinear, it is very difficult to accurately model the process for real-time control. In this paper, a discrete-time transfer function matrix model for gas metal arc welding process is proposed. Although this linearized model is valid only around the operating point of interest, the adaptation mechanism employed in the control system render this model useful over a wide operating range. A multivariable one-step-ahead adaptive control strategy combined with a recursive least-squares method for on-line parameter estimation is implemented in order to achieve the desired weld bead geometries. Command following and disturbance rejection properties of the adaptive control system for both SISO and MIMO cases are investigated by simulation and experiment.

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자기동조법에 의한 유전전동기의 강인한 속도 제어계 설계 (A Robust Speed Control System Design of Induction Motors Using Self-Tuning Control Method)

  • 김상봉;전봉환;정석권
    • 한국정밀공학회지
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    • 제12권8호
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    • pp.168-175
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    • 1995
  • A robust speed control algorithm under disturbances and reference change is developed using the self tuning control method in order to control induction motors. The method incorporates the concepts of the well known internal model principle and the annihilator polynomial. The effectiveness of the method is evaluated through the speed control experimental results of an induction motor for refernce change and arbitrary distrbance.

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DESIGN OF A PWR POWER CONTROLLER USING MODEL PREDICTIVE CONTROL OPTIMIZED BY A GENETIC ALGORITHM

  • Na, Man-Gyun;Hwang, In-Joon
    • Nuclear Engineering and Technology
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    • 제38권1호
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    • pp.81-92
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    • 2006
  • In this study, the core dynamics of a PWR reactor is identified online by a recursive least-squares method. Based on the identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to designing an automatic controller for the thermal power control of PWR reactors. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, this procedure for solving the optimization problem is repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired temperature, as well as minimizing the variation of the control rod positions. In addition, the objectives are subject to the maximum and minimum control rod positions as well as the maximum control rod speed. Therefore, a genetic algorithm that is appropriate for the accomplishment of multiple objectives is utilized in order to optimize the model predictive controller. A three-dimensional nuclear reactor analysis code, MASTER that was developed by the Korea Atomic Energy Research Institute (KAERI) , is used to verify the proposed controller for a nuclear reactor. From the results of a numerical simulation that was carried out in order to verify the performance of the proposed controller with a $5\%/min$ ramp increase or decrease of a desired load and a $10\%$ step increase or decrease (which were design requirements), it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.

유전자 알고리즘에 의해 최적화된 모델예측제어를 이용한 PWR 출력제어기 (A Pressurized Water Reactor Power Controller Using Model Predictive Control Optimized by a Genetic Algorithm)

  • 나만균;황인준
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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    • pp.104-106
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    • 2005
  • In this work, a PWR reactor core dynamics is identified online by a recursive least squares method. Based on this identified reactor model consisting of the control rod position and the core average coolant temperature, the future average coolant temperature is predicted. A model predictive control method is applied to design an automatic controller for thermal power control in PWRs. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize both the difference between the predicted core coolant temperature and the desired one, and the variation of the control rod positions. Also, the objectives are subject to maximum and minimum control rod positions and maximum control rod speed. Therefore, the genetic algorithm that is appropriate to accomplish multiple objectives is used to optimize the model predictive controller. A 3-dimensional nuclear reactor analysis code, MASTER that was developed by Korea Atomic Energy Research Institute (KAERI), is used to verify the proposed controller for a nuclear reactor. From results of numerical simulation to check the performance of the proposed controller at the 5%/min ramp increase or decrease of a desired load and its 10% step increase or decrease which are design requirements, it was found that the nuclear power level controlled by the proposed controller could track the desired power level very well.

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비정형성 등속운동 객체의 움직임 추정을 위한 블록기반 움직임 평활화 (Block-based Motion Vector Smoothing for Nonrigid Moving Objects)

  • 손영욱;강문기
    • 대한전자공학회논문지SP
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    • 제44권6호
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    • pp.47-53
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    • 2007
  • 블록 기반 프레임 레이트 변환 (frame-rate conversion) 또는 필름 떨림 보상 (film judder compensation)을 수행하기 위해서는 참 움직임 벡터(true motion vector)를 찾아야 한다. 이를 위해서 현재 블록의 공간적 및 시간적 상관성을 최대로 하여 시각적으로 덜 부자연스럽게 느끼도록 하는 방법들이 연구되었다. 그러나 기존의 블록단위 절대값 차이의 합 (SAD)만으로는 비정형성 객체의 움직임 에러를 추정할 수 없었다. 본 논문에서는 비정형성 객체가 등속운동을 하는 경우 재귀적으로 기존의 움직임을 유지하도록 하는 방법을 제안하였다. 현재 블록의 등속움직임 추정값을 재귀평균으로 구하였으며 현재 블록 벡터의 신뢰도를 계산하여 원래의 움직임 벡터와 재귀평균 움직임 벡터중에서 가중치를 두도록 하였다. 실험결과 비정형성 등속운동 객체의 움직임을 블록기반으로 추정함을 확인할 수 있었다.