• 제목/요약/키워드: linear filter

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XPTOS에 의한 디스크 드라이브 서보메커니즘의 구성시 BESSEL 필터 표준 함수에 근거한 상태피드백이득 결정 (The determination of state feedback gains of XPTOS for disk drive servomechanism based on BESSEL filter prototype)

  • 한권희;이자성
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.980-983
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    • 1996
  • This paper presents the method of determining state feedback gains of XPTOS for disk drive servomechanism based BESSEL filter prototype. A typical disk drive actuator can be modeled as second order dynamics for low frequencies. However, the response at higher frequencies shows resonant behavior which cannot be easily modeled. XPTOS consists of the nonlinear control region and the linear control region. In the linear control region, the poles of a second order nominal model of plant must be properly relocated by pole placement technique to attenuate resonant modes at high frequency and to attain minimum time state transition. It is difficult to select position to satisfy this object because velocity feedback gain is subjected to position feedback gain in XPTOS. Here poles of BESSEL filter prototype are selected to determine state feedback gains of XPTOS. Simulation results for disk drive servomechanism using XPTOS having state feedback gains by the proposed method are presented.

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Optimal Design for Hybrid Active Power Filter Using Particle Swarm Optimization

  • Alloui, Nada;Fetha, Cherif
    • Transactions on Electrical and Electronic Materials
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    • 제18권3호
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    • pp.129-135
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    • 2017
  • This paper introduces a design and a simulation of a hybrid active power filter (HAPF) for harmonics reduction given an ideal supply source. The synchronous reference frame method has been used here to identify the reference currents. The proposed HAPF uses a new artificial- intelligence technique called Particle Swarm Optimization (PSO) for tuning the parameters of a proportional and integral controller called PI-PSO. The PI-PSO controller is used to archive optimality for the DC-link voltage of the HAPF-inverter. The hysteresis non-linear current control method is used in this approach to compare the extracted reference and the actual currents in order to generate the pulse gate required for the HAPF. Results obtained by simulations with Matlab/Simuling show that the proposed approach is very flexible and effective for eliminating harmonic currents generated by the non-linear load with the HAPF based PSO tuning.

효과적인 적응 전처리왜곡기를 이용한 OFDM 시스템에서의 비선형 왜곡 보상 (On Compensating Nonlinear Distortions of an OFDM System Using an Efficient Adaptive Predistorter)

  • 강현우;조용수;윤대희
    • 한국통신학회논문지
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    • 제22권4호
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    • pp.696-705
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    • 1997
  • This paper presents an efficient adaptive predistortion technique compensating linear and nonlinear distortions caused by high-power amplifier (HPA) with memory in OFDM systems. The efficient adaptive data predistortion techniques proposed for compensation of HPA with memory in single carrier systems cannot be applied to OFDM systems since the possible input levels for HPA is infinite in OFDM systems. Also, previous adaptive predistortion techniques, based on Volterra series modeling, are not suitable for real-time implementation due to high computational burden and slow convergence rate. In the proposed approach, the memoryless HPA preceded by a linear filter in OFDM systems is modeled by the Wiener system which is then precompensated by the proposed adaptive predistorter with a minimum number of filter taps. An adaptive algorithm for adjusting the proposed adaptive predistorter is derived using the stochastic gradient method. It is demonstrated by computer simulation that the performance of OFDM system suffering from nonlinear distortion can be greatly improved by the proposed efficient adaptive predistorter using a small number of filter taps.

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Structural identification based on incomplete measurements with iterative Kalman filter

  • Ding, Yong;Guo, Lina
    • Structural Engineering and Mechanics
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    • 제59권6호
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    • pp.1037-1054
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    • 2016
  • Structural parameter evaluation and external force estimation are two important parts of structural health monitoring. But the structural parameter identification with limited input information is still a challenging problem. A new simultaneous identification method in time domain is proposed in this study to identify the structural parameters and evaluate the external force. Each sampling point in the time history of external force is taken as the unknowns in force evaluation. To reduce the number of unknowns for force evaluation the time domain measurements are divided into several windows. In each time window the structural excitation is decomposed by orthogonal polynomials. The time-variant excitation can be represented approximately by the linear combination of these orthogonal bases. Structural parameters and the coefficients of decomposition are added to the state variable to be identified. The extended Kalman filter (EKF) is augmented and selected as the mathematical tool for the implementation of state variable evaluation. The proposed method is validated numerically with simulation studies of a time-invariant linear structure, a hysteretic nonlinear structure and a time-variant linear shear frame, respectively. Results from the simulation studies indicate that the proposed method is capable of identifying the dynamic load and structural parameters fairly accurately. This method could also identify the time-variant and nonlinear structural parameter even with contaminated incomplete measurement.

Novel Pilot-Assisted Channel Estimation Techniques for 3GPP LTE Downlink with Performance-Complexity Evaluation

  • 칭양;휘빙;장경희
    • 한국통신학회논문지
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    • 제35권7A호
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    • pp.623-631
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    • 2010
  • In this paper, various of pilot-assisted channel estimation techniques for 3GPP LTE downlink are tested under multipath Rayleigh fading channel. At first, the conventional channel estimation techniques are applied with linear zero-forcing (ZF) equalizer, such as one dimensional least square (1-D LS) linear interpolation, two dimensional (2-D) wiener filter, the time and frequency dimension separate wiener filter and maximum likelihood estimator (MLE). Considering the practical implementation, we proposed two channel estimation techniques by combining time-dimension wiener filter and MLE in two manners, which showed a good tradeoff between system performance and complexity when comparing with conventional techniques. The nonlinear decision feedback equalizer (DFE) which can show a better performance than linear ZF equalizer is also implemented for mitigating inter-carrier interference (ICI) in our system. The complexity of these algorithms are calculated in terms of the number of complex multiplications (CMs) and the performances are evaluated by showing the bit error rate (BER).

관성 센서를 이용한 휴머노이드 로봇용 3축 자세 추정 알고리듬 개발 (Development of 3-Dimensional Pose Estimation Algorithm using Inertial Sensors for Humanoid Robot)

  • 이아람;김정한
    • 제어로봇시스템학회논문지
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    • 제14권2호
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    • pp.133-140
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    • 2008
  • In this paper, a small and effective attitude estimation system for a humanoid robot was developed. Four small inertial sensors were packed and used for inertial measurements(3D accelerometer and three 1D gyroscopes.) An effective 3D pose estimation algorithm for low cost DSP using an extended Kalman filter was developed and evaluated. The 3D pose estimation algorithm has a very simple structure composed by 3 modules of a linear acceleration estimator, an external acceleration detector and an pseudo-accelerometer output estimator. The algorithm also has an effective switching structure based on probability and simple feedback loop for the extended Kalman filter. A special test equipment using linear motor for the testing of the 3D pose sensor was developed and the experimental results showed its very fast convergence to real values and effective responses. Popular DSP of TMS320F2812 was used to calculate robot's 3D attitude and translated acceleration, and the whole system were packed in a small size for humanoids robots. The output of the 3D sensors(pitch, roll, 3D linear acceleration, and 3D angular rate) can be transmitted to a humanoid robot at 200Hz frequency.

비선형매핑 기반 뇌-기계 인터페이스를 위한 신경신호 spike train 디코딩 방법 (Neuronal Spike Train Decoding Methods for the Brain-Machine Interface Using Nonlinear Mapping)

  • 김경환;김성신;김성준
    • 대한전기학회논문지:시스템및제어부문D
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    • 제54권7호
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    • pp.468-474
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    • 2005
  • Brain-machine interface (BMI) based on neuronal spike trains is regarded as one of the most promising means to restore basic body functions of severely paralyzed patients. The spike train decoding algorithm, which extracts underlying information of neuronal signals, is essential for the BMI. Previous studies report that a linear filter is effective for this purpose and there is no noteworthy gain from the use of nonlinear mapping algorithms, in spite of the fact that neuronal encoding process is obviously nonlinear. We designed several decoding algorithms based on the linear filter, and two nonlinear mapping algorithms using multilayer perceptron (MLP) and support vector machine regression (SVR), and show that the nonlinear algorithms are superior in general. The MLP often showed unsatisfactory performance especially when it is carelessly trained. The nonlinear SVR showed the highest performance. This may be due to the superiority of the SVR in training and generalization. The advantage of using nonlinear algorithms were more profound for the cases when there are false-positive/negative errors in spike trains.

An improved Kalman filter for joint estimation of structural states and unknown loadings

  • He, Jia;Zhang, Xiaoxiong;Dai, Naxin
    • Smart Structures and Systems
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    • 제24권2호
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    • pp.209-221
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    • 2019
  • The classical Kalman filter (KF) provides a practical and efficient way for state estimation. It is, however, not applicable when the external excitations applied to the structures are unknown. Moreover, it is known the classical KF is only suitable for linear systems and can't handle the nonlinear cases. The aim of this paper is to extend the classical KF approach to circumvent the aforementioned limitations for the joint estimation of structural states and the unknown inputs. On the basis of the scheme of the classical KF, analytical recursive solution of an improved KF approach is derived and presented. A revised form of observation equation is obtained basing on a projection matrix. The structural states and the unknown inputs are then simultaneously estimated with limited measurements in linear or nonlinear systems. The efficiency and accuracy of the proposed approach is verified via a five-story shear building, a simply supported beam, and three sorts of nonlinear hysteretic structures. The shaking table tests of a five-story building structure are also employed for the validation of the robustness of the proposed approach. Numerical and experimental results show that the proposed approach can not only satisfactorily estimate structural states, but also identify unknown loadings with acceptable accuracy for both linear and nonlinear systems.

Kalman Filter-based Navigation Algorithm for Multi-Radio Integrated Navigation System

  • Son, Jae Hoon;Oh, Sang Heon;Hwang, Dong-Hwan
    • Journal of Positioning, Navigation, and Timing
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    • 제9권2호
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    • pp.99-115
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    • 2020
  • Since GNSS is easily affected by jamming and/or spoofing, alternative navigation systems can be operated as backup system to prepare for outage of GNSS. Alternative navigation systems are being researched over the world, and a multi-radio integrated navigation system using alternative navigation systems such as KNSS, eLoran, Loran-C, DME, VOR has been researched in Korea. Least Square or Kalman filter can be used to estimate navigation parameters in the navigation system. A large number of measurements of the Kalman filter may lead to heavy computational load. The decentralized Kalman filter and the federated Kalman filter were proposed to handle this problem. In this paper, the decentralized Kalman filter and the federated Kalman filter are designed for the multi-radio integrated navigation system and the performance evaluation result are presented. The decentralized Kalman filter and the federated Kalman filter consists of local filters and a master filter. The navigation parameter is estimated by local filters and master filter compensates navigation parameter from the local filters. Characteristics of three Kalman filters for a linear system and nonlinear system are investigated, and the performance evaluation results of the three Kalman filters for multi-radio integrated navigation system are compared.

바커 코드에 대한 최적 부엽 억제 필터의 설계에 관한 연구 (A Study on the Design of Optimum Sidelobe Suppression Filter for Barker Codes)

  • 정경태
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1991년도 학술발표회 논문집
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    • pp.151-156
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    • 1991
  • In this paper, we propose a new algorithm for designing the R-G filter that has optimum performance in terms of mean square sidelobe level(MSSL) for the Barker code. The advantage of the conventional R-G filter lies in its simple structure so that it can be easily implemented. However, the conventional R-G filter dose not have optimum performances in terms of peak sidelobe level(PSL), mean sidelobe level(MSL), and MSSL. Recently, a(R-G)LP filter of which filter coefficients are obtained by the linear programming algorithm was proposed and known to have optimum performance in PSL. The proposed (R-G)LS filter keeps the simple structure of the conventional R-G filter and has the filter coefficients that minimizes the sidelobe in the least square sense. The analytic results show that the proposed (R-G)LS filter has better performances than the conventional R-G filter in terms of PSL, MSL, and MSSL. Compared with (R-G)LP filter, the proposed (R-G)LS filter has better performances in terms of MSL and MSSL. The proposed filter design algorithm can be applied to the other binary codes such as truncated pseudonoise(PN) codes and concatenated codes.

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