• Title/Summary/Keyword: Nonlinear estimation

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Nonlinear Adaptive Control for Linear Motor through the Estimation of Friction Forces and Force Ripples (마찰력 및 리플력 추정을 통한 리니어 모터의 비선형 적응제어)

  • Kim, Hong-Bin;Lee, Byong-Huee;Han, Sang-Oh;Huh, Kun-Soo
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.31 no.1 s.256
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    • pp.18-25
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    • 2007
  • Linear motor is easily affected by load disturbance, force ripple, friction, and parameter variations because there is no mechanical transmission to reduce the effects of model uncertainties and external disturbance. These nonlinear effects have been reduced for high-speed/high-accuracy position control either through the better motor design or via the better control algorithm that can compensate the nonlinear effects. In this paper, a nonlinear adaptive control algorithm is designed and applied for the position control of permanent magnet linear synchronous motor. In order to estimate and compensate the nonlinear effects such as friction and force ripple, the estimation and the nonlinear adaptive control laws are derived based on the virtual control input and a suitable Lyapunov function. The proposed controller is evaluated through the computer simulations. The control algorithm is also implemented to a DSP board and interfaced to the PMLSM for verifying the realtime control performance.

Target Localization using Combination of the IV and QCLS Method in the Sensor Network (센서네트워크 내의 IV 기법과 QCLS 기법을 결합한 위치 추정)

  • Kim, Yong-Hwi;Choi, Ga-Hyoung;Yoon, Tae-Sung;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.1768-1769
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    • 2011
  • The nonlinear estimation and the pseudo-linear estimation are used to treat the target localization in sensor network which provides range difference of arrival (RDOA) measurements. It is known that the nonlinear estimation has sensitive problem for the initial estimate and the pseudo-linear estimation has a large estimation error. The QCLS method is the typical estimator of the methods for pseudo-linear estimation. However the estimate by using the QCLS method includes the estimation error because the first stage of two estimation processes of the QCLS method causes the biased estimation error. Therefore we propose a instrumental variables(IV) method for minimizing the estimation error of the first stage. The simulation shows that the performance of the proposed method is superior to the QCLS method.

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Nonlinear Parameter Estimation of Suspension System (현가장치의 비선형 설계변수 추정)

  • 박주표;최연선
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.05a
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    • pp.281-286
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    • 2003
  • A Suspension system of a car is composed of dampers and springs. The dampers and springs usually have nonlinear characteristics. However, the nonlinear characteristics of the springs and dampers through analytical model cannot agree with the experimental results. Therefore, the nonlinearity of the suing and damper should be known from the experimental results. In this study, the methods of system identification for nonlinear dynamic system in time domain are discussed and the nonlinear parameter estimation lot experimental data of an EF-SONATA car was done. The results show that a cubic and a coupled term should be considered to model the suspension system.

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Evolution Strategies Based Particle Filters for Simultaneous State and Parameter Estimation of Nonlinear Stochastic Models

  • Uosaki, K.;Hatanaka, T.
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1765-1770
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    • 2005
  • Recently, particle filters have attracted attentions for nonlinear state estimation. In this approaches, a posterior probability distribution of the state variable is evaluated based on observations in simulation using so-called importance sampling. We proposed a new filter, Evolution Strategies based particle (ESP) filter to circumvent degeneracy phenomena in the importance weights, which deteriorates the filter performance, and apply it to simultaneous state and parameter estimation of nonlinear state space models. Results of numerical simulation studies illustrate the applicability of this approach.

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A study on the effect of inverter nonlinear characteristic on the flux estimation of an induction motor (인버터의 비선형 특성이 유도전동기의 자속 추정에 미치는 영향에 대한 연구)

  • Kim, Sang-Hoon;Kim, Tae-Suk
    • Journal of Industrial Technology
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    • v.28 no.B
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    • pp.167-174
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    • 2008
  • In this paper, the analysis on type effect of inverter output voltage distortion on the control of an induction motor is discussed. The inverter output voltage is distorted differently from the reference voltage owing to the inverter nonlinear characteristic. The inverter nonlinear characteristic results from the voltage drop, the inherent characteristic of the power semiconductor, and the dead time for preventing the short circuit of the inverter leg. This characteristic distorts the inverter output voltage and then, causes the motor flux estimation error. Although this characteristics do not significantly effect in the general-purpose induction motor control, but significantly effect on the low-speed operation of high performance motor control such as the sensorless vector control.

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An estimation technique for nonlinear distortion in high-density magnetic recording channels (고밀도 자기 기록 채널의 비선형 왜곡 추정 기법)

  • 이남진;오대선;조용수;김기호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.11
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    • pp.2439-2450
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    • 1997
  • As recording densities increase in digital magnetic recording channels, the performances of digital detection techniques such as PRML and DFE degrade significantly due to nonlinear distortion in recording channels. The primary impediments for hgih-density recording are generally classified as nonlinear transition shift, which can be reduced substantially by the precompensation technique, and partial erasure which usually requires sophisticated nonlinear equalization techniques. In order to acheieve the highest density recording, accurate estimation of the parameters associated with these two noninear distortions is crucial. In this paper, a new estimation technique to distinguish these two different nonlinear effect using a proposed adaptive algorithm in time domain is presented. The effectiveness of the proposed adaptive approach to identify uniquely the nonlinear parameter with bias is demonstrated by computer simulation.

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Seismic Damage Assessment and Nonlinear Structural Identification Using Measured Seismic Responses (실측 지진응답을 이용한 지진손상도 평가 및 소성모형 추정)

  • 이형진;김남식
    • Journal of the Earthquake Engineering Society of Korea
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    • v.6 no.6
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    • pp.7-15
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    • 2002
  • In this paper, the nonlinear parameter estimation method using the estimated hysteresis of each structural members was studied for the purpose of efficient seismic damage prediction and estimation of MDOF nonlinear structural model in the shaking table test. The hysteresis of each structural members can be obtained by the conversion of measured response histories into relative motions of each structural members and member forces. These hysteresis can be used to evaluate various kinds of damage indices of each structural members. The MDOF nonlinear structural model for further analysis(re-analysis) can be easily reconstructed using estimated nonlinear structural parameters of each structural members. To demonstrate the proposed techniques, several numerical and experimental example analyses are carried out. The results indicate that the proposed method can be very useful to assess local seismic damages of structures.

A Nonlinear Speed Control for a PM Synchronous Motor Using a Simple Disturbance Estimation Technique

  • Lee Na-Young;Kim Kyeong-Hwa;Youn Myung-Joong
    • Proceedings of the KIPE Conference
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    • 2001.10a
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    • pp.326-330
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    • 2001
  • A nonlinear speed control for a permanent magnet (PM) synchronous motor using a simple disturbance estimation technique is presented. By using a feedback linearization, scheme, the nonlinear motor model can be linearized. To compensate an undesirable output performance under the mismatch of the system parameters and load conditions the controller parameters will be estimated by using a disturbance observer theory. Since only the two reduced-order observers are used for the parameter estimation, the observer designs are considerably simple and the computational load of the controller for parameter estimation is negligibly small. The proposed control scheme is implemented on a PM synchronous motor using DSP TMS320C31 and the effectiveness is verified through the comparative experiments.

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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.

Sensorless IPMSM Control Based on an Extended Nonlinear Observer with Rotational Inertia Adjustment and Equivalent Flux Error Compensation

  • Mao, Yongle;Yang, Jiaqiang;Yin, Dejun;Chen, Yangsheng
    • Journal of Power Electronics
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    • v.16 no.6
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    • pp.2150-2161
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    • 2016
  • Mechanical and electrical parameter uncertainties cause dynamic and static estimation errors of the rotor speed and position, resulting in performance deterioration of sensorless control systems. This paper applies an extended nonlinear observer to interior permanent magnet synchronous motors (IPMSM) for the simultaneous estimation of the rotor speed and position. Two compensation methods are proposed to improve the observer performance against parameter uncertainties: an on-line rotational inertia adjustment approach that employs the gradient descent algorithm to suppress dynamic estimation errors, and an equivalent flux error compensation approach to eliminate static estimation errors caused by inaccurate electrical parameters. The effectiveness of the proposed control strategy is demonstrated by experimental tests.