• 제목/요약/키워드: State Estimator

검색결과 309건 처리시간 0.031초

지연 입력을 가진 서보시스템의 상태 추정자 설계 (The State Estimator Design for Servo system with Delayed Input)

  • 신두진;공정자;허욱열
    • 대한전기학회논문지:전력기술부문A
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    • 제48권5호
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    • pp.607-614
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    • 1999
  • This paper deals with the design problem of the state estimator for servo system. The servo system has input time delay which depends on the computational time of control algorithm. The delayed input is a factor that brings out the state estimation error. So in order to reduce the state estimation error of the system, we propose a state estimator in which the delayed input of the system is considered. For this purpose, discrete time state space model is established accounting for the delayed input and a state estimator is designed based on this model. Kalman filter algorithm is employed in the design of the state estimator. The proposed estimator is used in the speed control of servo system with delayed input. Performance of the proposed state estimator is exemplified via simulations and experiments for servo system. Also, robustness of the proposed estimator to modeling error by variation of the system parameters is also shown in simulations.

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섭동관측기를 연합한 강인 상태추정기 설계 및 해석 (Design and Analysis of a Robust State Estimator Combining Perturbation Observer)

  • 권상주
    • 제어로봇시스템학회논문지
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    • 제11권6호
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    • pp.477-483
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    • 2005
  • This article describes a robust state estimation method which enables to produce reliable estimates in spite of heavy perturbation including plant uncertainty and external disturbances. The main idea is to combine the standard state estimator with the perturbation observer in the estimator frame. The perturbation observer reflects equivalent quantity of plant uncertainty and external disturbances during the estimation process so that the state estimator dynamics gets as close as possible to the real plant dynamics. The robust state estimator proposed in this paper is given in a recursive discrete-time form which is very useful fur implementation purpose. In terms of the error dynamics derived for the robust state estimator, we discuss the stability issue and noise sensitivity. The effectiveness and practicality of the robust state estimator are verified through numerical examples and experimental results.

지연입력을 가진 서보시스템의 상태추정자 설계 (A state estimator design for servo system with delayed input)

  • 공정자;허욱열;정갑균
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 B
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    • pp.537-540
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    • 1998
  • This thesis deals with the design problem of the state estimator for digital servo system. Digital servo system has input time delay, which depends on the size of control algorithm. The delayed input is a factor that brings out the state estimation error. So, in order to reduce this state estimation error of the system, we proposes a state estimator in which the delayed input of the system is considered. At first, a discrete-time state-space model is established accounting for the delayed input. Next, the state estimator is designed based on this model. we employ Kalman filter algorithm in design of the state estimator. The performance of proposed state estimator is exemplified via some simulations and experiment for servo system. And robustness of the proposed estimator to modelling error by variation of the system parameter is also shown in these simulations.

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차량 전복 방지를 위한 강건한 롤 상태 추정기 설계 (Design of a Robust Estimator for Vehicle Roll State for Prevention of Vehicle Rollover)

  • 박지인;이경수
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2007년도 춘계학술대회A
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    • pp.1103-1108
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    • 2007
  • This paper describes a robust model-based roll state estimator for application to the detection of impending vehicle rollover. The roll state estimator is based on a 2-D bicycle model and a roll model to estimate the maneuver-induced vehicle roll motion. The measurement signals are lateral acceleration, yaw rate, steering angle, and vehicle speed. Vehicle mass is adapted to obtain robust performance of the estimator. Computer simulation is conducted to evaluate the proposed roll state estimator by using a validated vehicle simulator. It is shown that the roll state estimator shows robust performance without exact vehicle mass information.

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퍼지신경망과 강인한 마찰 상태 관측기를 이용한 비선형 마찰 서보시스템에 대한 강인 제어 (Robust Control for Nonlinear Friction Servo System Using Fuzzy Neural Network and Robust Friction State Observer)

  • 한성익
    • 한국정밀공학회지
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    • 제25권12호
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    • pp.89-99
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    • 2008
  • In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

이산형 칼만 필터를 이용한 서보 시스템의 상태 추정자 설계 (A State Estimator for servo system using discrete Kalman Filter)

  • 신두진;염형선;허욱열;이제희
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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    • pp.420-422
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    • 1998
  • In this paper, we propose a position-speed control of servo system with a state estimator. And also we utilized two mass modelling in order to deals with real system accurately. The overall control system consists of two parts: the position-speed controller and state estimator. The Kalman filter applied as state - feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear,unbiased and minimun error variance recursive algorithm to estimate the unknown state optimally. Therefore we consider the error problem about the servo system modelling, the measurement noise at low-speed ranges a stochastic system, and implement a optimal state observer. Performance of the proposed state estimator are demonstrated by computer simulations.

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강인한 마찰 상태 관측기와 순환형 퍼지신경망 관측기를 이용한 비선형 마찰제어 (Nonlinear Friction Control Using the Robust Friction State Observer and Recurrent Fuzzy Neural Network Estimator)

  • 한성익
    • 한국공작기계학회논문집
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    • 제18권1호
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    • pp.90-102
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    • 2009
  • In this paper, a tracking control problem for a mechanical servo system with nonlinear dynamic friction is treated. The nonlinear friction model contains directly immeasurable friction state and the uncertainty caused by incomplete modeling and variations of its parameter. In order to provide the efficient solution to these control problems, we propose a hybrid control scheme, which consists of a robust friction state observer, a RFNN estimator and an approximation error estimator with sliding mode control. A sliding mode controller and a robust friction state observer is firstly designed to estimate the unknown infernal state of the LuGre friction model. Next, a RFNN estimator is introduced to approximate the unknown lumped friction uncertainty. Finally, an adaptive approximation error estimator is designed to compensate the approximation error of the RFNN estimator. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are presented. Results demonstrate the remarkable performance of the proposed control scheme.

유압 서보시스템의 속도제어를 위한 관측기 설계에 관한 연구 (A Study on the Design of Estimator for Velocity Control of Electro-hydraulic Servo System)

  • 송창섭;윤장상;신대영
    • 한국정밀공학회지
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    • 제8권3호
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    • pp.64-72
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    • 1991
  • This paper deals with the state estimator and controller. All state variables' feedback in the system were used to improve electro hydraulic servo sysem were used to improve electro hydraulic servo system's responese charact- eristics. Many gains of the state variables'and estimator's are produced by the algebraic Riccati equation, and every state variables'optimal gain and estimator gain is selected by trial and error method. For the designed estimator performance's examination, this paper simulate the time response for the step input, the reduced velocity output in subjected to load torque, and the time response for the step input in changing the inertiamoment.

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Training an Artificial Neural Network for Estimating the Power Flow State

  • Sedaghati, Alireza
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.275-280
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    • 2005
  • The principal context of this research is the approach to an artificial neural network algorithm which solves multivariable nonlinear equation systems by estimating the state of line power flow. First a dynamical neural network with feedback is used to find the minimum value of the objective function at each iteration of the state estimator algorithm. In second step a two-layer neural network structures is derived to implement all of the different matrix-vector products that arise in neural network state estimator analysis. For hardware requirements, as they relate to the total number of internal connections, the architecture developed here preserves in its structure the pronounced sparsity of power networks for which state the estimator analysis is to be carried out. A principal feature of the architecture is that the computing time overheads in solution are independent of the dimensions or structure of the equation system. It is here where the ultrahigh-speed of massively parallel computing in neural networks can offer major practical benefit.

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Time-delayed State Estimator for Linear Systems with Unknown Inputs

  • Jin Jaehyun;Tahk Min-Jea
    • International Journal of Control, Automation, and Systems
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    • 제3권1호
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    • pp.117-121
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    • 2005
  • This paper deals with the state estimation of linear time-invariant discrete systems with unknown inputs. The forward sequences of the output are treated as additional outputs. In this case, the rank condition for designing the unknown input estimator is relaxed. The gain for minimal estimation error variance is presented, and a numerical example is given to verify the proposed unknown input estimator.