• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.1
• /
• pp.34-39
• /
• 2015

In this paper, a finite impulse response (FIR) filter is proposed for discrete-time nonlinear systems. The proposed filter is designed by combining the estimate of the perturbation state and nominal state. The perturbation state is estimated by adapting the optimal time-varying FIR filter for the linearized perturbation model and the nominal state is directly obtained from the nonlinear nominal trajectory model. Since the FIR structured estimators use the finite horizon information on the most recent time interval, the proposed extended FIR filter satisfies the bounded input/bounded output (BIBO) stability, which can't be obtained from infinite impulse response (IIR) estimators. Thus, it can be expected that the proposed extended FIR filter is more robust than IIR structured estimators such as an extended Kalman filter for the round-of errors and the uncertainties from unknown initial states and uncertain system model parameters. The simulation results show that the proposed filter has better performance than the extended Kalman filter (EKF) in both robustness and fast convergency.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.980-983
• /
• 1996

A new version of the discrete-time optimal FIR (finite impulse response) filter utilizing only the measurements of finite sliding estimation window is suggested for linear time-invariant state-space models. This filter is called the BLUFIR (best linear unbiased finite impulse response) filter since it provides the BLUE (best linear unbiased estimate) of the state obtained from the measurements of the estimation window. It is shown that the BLUFIR filter has the deadbeat property when there are no noises in the estimation window.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.413-418
• /
• 2003

In this paper, a new multirate optimal finite impulse response (FIR) filter is proposed for the signal reconstruction in the nosy filter bank systems. The multirate optimal FIR filter replaces the conventional synthesis filters and the Kalman synthesis filter. First, the generic linear model is derived from the multirate state space model for an autoregressive (AR)input signal. Second, the multirate optimal FIR filter is derived from the multirate generic linear model using the minimum variance criterion. This paper also provides numerical examples and results. The simulation results illustrate that the performance is improved compared with conventional synthesis filters and the proposed filter has advantages over the Kalman synthesis filter.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.12
• /
• pp.1183-1187
• /
• 2011

In this paper, an optimal FIR (Finite-Impulse-Response) filter is proposed for discrete time-varying state-space models. The proposed filter estimates the current state using measured output samples on the recent time horizon so that the variance of the estimation error is minimized. It is designed to be linear, unbiased, with an FIR structure, and is independent of any state information. Due to its FIR structure, the proposed filter is believed to be robust for modeling uncertainty or numerical errors than other IIR filters, such as the Kalman filter. For a general system with system and measurement noise, the proposed filter is derived without any artificial assumptions such as the nonsingular assumption of the system matrix A and any infinite covariance of the initial state. A numerical example show that the proposed FIR filter has better performance than the Kalman filter based on the IIR (Infinite- Impulse-Response) structure when modeling uncertainties exist.

• Proceedings of the IEEK Conference
• /
• 1999.11a
• /
• pp.173-176
• /
• 1999

Frequency responses of the surface acoustic wave(SAW) filters are simulated by using the impulse modeling. The simulation technique of the SAW filters is to use the Fourier transformation to make a correspondence between the impulse response of the filter and the taps in the delay line. Since the Fourier series must be truncated after a finite number of terms, window functions are often used to weight the coefficients to obtain the desirable side-lobe level and bandwidth. The filter design is operated through the iterative simulation procedures. The design process is capable of yielding filters with optimized frequency response characteristics.

• Journal of Mechanical Science and Technology
• /
• v.15 no.2
• /
• pp.232-238
• /
• 2001

Fast Fourier Transformation is employed to convert the head variation of a pipeline in the time domain to the amplitude of the frequency domain. Applying method of characteristics to a pipeline provides a significant frequency range for a surge introduced from the valve modulation. Inverse Fast Fourier Transformation and a Finite Impulse Response Filter can be used to remove any possible noise existing from the significant frequency range of an unsteady condition. A filtered signal shows higher potential for the inverse calculation of leakage detection than the noise-added signal does. The respective performances of Inverse Fast Fourier Transformation and a Finite Impulse Response Filter are compared in terms of leakage detection capability. Characteristics of the frequency range for multiple leakages were investigated to validate the effectiveness of the noise control method in the frequency domain.

• International journal of advanced smart convergence
• /
• v.4 no.2
• /
• pp.138-144
• /
• 2015

Digital filters are extensively used in the world of communication. In order to design a digital finite impulse response (FIR) filter that satisfies all the required conditions is challenging. In this paper, design techniques of digital low pass FIR filters using Rectangular window method, Hamming window, Hanning window, and Optimal Parks McClellan method are presented. The stability, number of components required and filter coefficients are demonstrated for different design techniques. It is demonstrated that filter design using hamming window is comparatively better than rectangular and hanning window though the components required for all of the windowing technique are same, hamming shows higher stability. The stability is shown with the help of magnitude and phase spectrum of each window. Simulation is carried out using MATLAB and comparisons are made entirely based on the output of the simulation.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2548-2551
• /
• 2005

In this paper, a robust receding horizon finite impulse response(FIR) filter is proposed for a class of linear discrete time systems with uncertainty satisfying an integral quadratic constraint. The robust state estimation problem involves constructing the set of all possible states at the current time consistent with given system input, output measurements and the integral quadratic constraint.

• JSTS:Journal of Semiconductor Technology and Science
• /
• v.16 no.3
• /
• pp.261-273
• /
• 2016

Reconfigurable finite impulse response (FIR) filters whose filter coefficients and filter order change dynamically during run-time play an important role in the software defined radio (SDR) systems, multi-channel filters, and digital up/down converters. However, there are not many reports on such reconfigurable designs which can support dynamic variation of filter order and filter coefficients. The purpose of this paper is to provide an architectural solution for the FIR filters to support run-time variation of the filter order and filter coefficients. First, two straightforward designs, namely, (i) single-MAC based design and (ii) full-parallel design are presented. For large variation of the filter order, two designs based on (iii) folded structure and (iv) fast FIR algorithm are presented. Finally, we propose (v) high throughput design which provides significant advantage in terms of hardware and/or time complexities over the other designs. We compare complexities of all the five structures, and provide the synthesis results for verification.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.3
• /
• pp.437-447
• /
• 2003

We propose the methods to design the finite impulse response (FIR) and the infinite impulse response (IIR) lattice filters using Schur algorithm through the spectral factorization of the covariance matrix by circulant matrix factorization (CMF). Circulant matrix factorization is also very powerful tool used fur spectral factorization of the covariance polynomial in matrix domain to obtain the minimum phase polynomial without the polynomial root finding problem. Schur algorithm is the method for a fast Cholesky factorization of Toeplitz matrix, which easily determines the lattice filter parameters. Examples for the case of the FIR Inter and for the case of the IIR filter are included, and performance of our method check by comparing of our method and another methods (polynomial root finding and cepstral deconvolution).