Application of Kautz Models for Adaptive Vibration Control

2001 ◽  
Author(s):  
Dirk Mayer ◽  
Sven Herold ◽  
Holger Hanselka
Keyword(s):  
Vibration Control ◽  
Impulse Response ◽  
Adaptive Filter ◽  
Finite Impulse Response ◽  
Active Vibration Control ◽  
Active Noise Control ◽  
Lms Algorithm ◽  
Infinite Impulse Response ◽  
Fir Filters ◽  
Allpass Filters

Abstract Both for active noise control (ANC) and active vibration control (AVC) the well known F-X-LMS-algorithm can be used. This approach requires a proper model of the path from the actuator to the error sensor, preferably received with an on-line identification. In the field of ANC adaptive finite impulse response (FIR) filters work well for this task, but for lightly damped mechanical systems with long impulse responses FIR filters with up to several thousand coefficients would have to be used. One alternative are adaptive IIR filters, but these can get unstable while adapting or the adapting process can get stuck in local minima. In this work, adaptive Kautz models are introduced, which need some a priori knowledge about the poles of the system. On the other hand, they represent an infinite impulse response while maintaining the transversal structure of the adaptive filter. This is reached by generalization of the FIR filter, for which the delay operator is substituted by discrete allpass filters, the Kautz filters. The adaptive filter bank is implemented by means of the straightforward LMS algorithm in the Matlab/Simulink environment. As an example, system identification with Kautz models and their usage in AVC for a simple mechanical system will be studied.

A numerical and experimental implementation and integration of Steiglitz–McBride algorithm with the frequency domain IIR filtering technique for active vibration control

2016 ◽  
Vol 24 (6) ◽  
pp. 1086-1100
Author(s):  
Utku Boz ◽  
Ipek Basdogan
Keyword(s):  
Computational Complexity ◽  
Vibration Control ◽  
Frequency Domain ◽  
Impulse Response ◽  
Time Domain ◽  
Vibration Suppression ◽  
Active Vibration Control ◽  
Infinite Impulse Response ◽  
Iir Filter ◽  
Active Vibration

In adaptive control applications for noise and vibration, finite ımpulse response (FIR) or ınfinite ımpulse response (IIR) filter structures are used for online adaptation of the controller parameters. IIR filters offer the advantage of representing dynamics of the controller with smaller number of filter parameters than with FIR filters. However, the possibility of instability and convergence to suboptimal solutions are the main drawbacks of such controllers. An IIR filtering-based Steiglitz–McBride (SM) algorithm offers nearly-optimal solutions. However, real-time implementation of the SM algorithm has never been explored and application of the algorithm is limited to numerical studies for active vibration control. Furthermore, the prefiltering procedure of the SM increases the computational complexity of the algorithm in comparison to other IIR filtering-based algorithms. Based on the lack of studies about the SM in the literature, an SM time-domain algorithm for AVC was implemented both numerically and experimentally in this study. A methodology that integrates frequency domain IIR filtering techniques with the classic SM time-domain algorithm is proposed to decrease the computational complexity. Results of the proposed approach are compared with the classical SM algorithm. Both SM and the proposed approach offer multimodal vibration suppression and it is possible to predict the performance of the controller via simulations. The proposed hybrid approach ensures similar vibration suppression performance compared to the classical SM and offers computational advantage as the number of control filter parameters increases.

Comparison of Infinite Impulse Response (IIR) and Finite Impulse Response (FIR) Filters in Cardiac Optical Mapping Records

2021 ◽  
pp. 207-224
Author(s):  
David Rivas-Lalaleo ◽  
Sergio Muñoz-Romero ◽  
Monica Huerta ◽  
Víctor Bautista-Naranjo ◽  
Jorge García-Quintanilla ◽  
...  
Keyword(s):  
Impulse Response ◽  
Optical Mapping ◽  
Finite Impulse Response ◽  
Infinite Impulse Response ◽  
Fir Filters

scholarly journals Adaptive Parameter Estimation of IIR System-Based WSN Using Multihop Diffusion in Distributed Approach

2020 ◽  
Vol 14 (4) ◽  
pp. 30-41
Author(s):  
Meera Dash ◽  
Trilochan Panigrahi ◽  
Renu Sharma ◽  
Mihir Narayan Mohanty
Keyword(s):  
Impulse Response ◽  
Sensor Node ◽  
Finite Impulse Response ◽  
Lms Algorithm ◽  
Sensor System ◽  
Superior Performance ◽  
Estimation Accuracy ◽  
Infinite Impulse Response ◽  
Communication Overhead ◽  
Least Mean Square

Distributed estimation of parameters in wireless sensor networks is taken into consideration to reduce the communication overhead of the network which makes the sensor system energy efficient. Most of the distributed approaches in literature, the sensor system is modeled with finite impulse response as it is inherently stable. Whereas in real time applications of WSN like target tracking, fast rerouting requires, infinite impulse response system (IIR) is used to model and that has been chosen in this work. It is assumed that every sensor node is equipped with IIR adaptive system. The diffusion least mean square (DLMS) algorithm is used to estimate the parameters of the IIR system where each node in the network cooperates themselves. In a sparse WSN, the performance of a DLMS algorithm reduces as the degree of the node decreases. In order to increase the estimation accuracy with a smaller number of iterations, the sensor node needs to share their information with more neighbors. This is feasible by communicating each node with multi-hop nodes instead of one-hop only. Therefore the parameters of an IIR system is estimated in distributed sparse sensor network using multihop diffusion LMS algorithm. The simulation results exhibit superior performance of the multihop diffusion LMS over non-cooperative and conventional diffusion algorithms.

scholarly journals Comparison of Motion Artefact Reduction Methods and the Implementation of Adaptive Motion Artefact Reduction in Wearable Electrocardiogram Monitoring

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1468
Author(s):  
Xiang An ◽  
George K. Stylios
Keyword(s):  
Impulse Response ◽  
Adaptive Filter ◽  
Finite Impulse Response ◽  
Median Filter ◽  
Infinite Impulse Response ◽  
Ecg Signal ◽  
Motion Artefact ◽  
Iir Filter ◽  
Adaptive Motion ◽  
Artefact Reduction

A motion artefact is a kind of noise that exists widely in wearable electrocardiogram (ECG) monitoring. Reducing motion artefact is challenging in ECG signal preprocessing because the spectrum of motion artefact usually overlaps with the very important spectral components of the ECG signal. In this paper, the performance of the finite impulse response (FIR) filter, infinite impulse response (IIR) filter, moving average filter, moving median filter, wavelet transform, empirical mode decomposition, and adaptive filter in motion artefact reduction is studied and compared. The results of this study demonstrate that the adaptive filter performs better than other denoising methods, especially in dealing with the abnormal ECG signal which is measured from a patient with heart disease. In the implementation of adaptive motion artefact reduction, the results show that the use of the impedance pneumography signal as the reference input signal for the adaptive filter can effectively reduce the motion artefact in the ECG signal.

scholarly journals Digital Finite Impulse Response Notch Filter with Non-Zero Initial Conditions, Based on an Infinite Impulse Response Prototype Filter

2012 ◽  
Vol 19 (4) ◽  
pp. 767-776 ◽  
Author(s):  
Sławomir Kocoń ◽  
Jacek Piskorowski
Keyword(s):  
Impulse Response ◽  
Narrow Band ◽  
Finite Impulse Response ◽  
Initial Conditions ◽  
Notch Filter ◽  
Infinite Impulse Response ◽  
Fir Filters ◽  
Ecg Signals ◽  
Prototype Filter ◽  
Power Line Noise

Abstract In this paper a concept of finite impulse response (FIR) narrow band-stop (notch) filter with non-zero initial conditions, based on infinite impulse response (IIR) prototype filter, is proposed. The filter described in this paper is used to suppress power line noise from ECG signals. In order to reduce the transient response of the proposed FIR notch filter, optimal initial conditions for the filter have been determined. The algorithm for finding the length of the initial conditions vector is presented. The proposed values of the length of initial conditions vector, for several ECG signals and interfering frequencies, are calculated. The proposed filters are tested using various ECG signals. Computer simulations demonstrate that the proposed FIR filters outperform traditional FIR filters with initial conditions set to zero.

scholarly journals NANO-studio, the design environment of filter banks implemented in standard CMOS technology

2021 ◽  
Author(s):  
Andrzej Handkiewicz ◽  
Mariusz Naumowicz
Keyword(s):  
Impulse Response ◽  
Filter Banks ◽  
Finite Impulse Response ◽  
Infinite Impulse Response ◽  
Cmos Process ◽  
Digital Cmos ◽  
Additional Advantage ◽  
Analysis And Synthesis ◽  
Optimization Parameters ◽  
Synthesis Filter

AbstractThe paper presents a method of optimizing frequency characteristics of filter banks in terms of their implementation in digital CMOS technologies in nanoscale. Usability of such filters is demonstrated by frequency-interleaved (FI) analog-to-digital converters (ADC). An analysis filter present in these converters was designed in switched-current technique. However, due to huge technological pitch of standard digital CMOS process in nanoscale, its characteristics substantially deviate from the required ones. NANO-studio environment presented in the paper allows adjustment, with transistor channel sizes as optimization parameters. The same environment is used at designing a digital synthesis filter, whereas optimization parameters are input and output conductances, gyration transconductances and capacitances of a prototype circuit. Transition between analog s and digital z domains is done by means of bilinear transformation. Assuming a lossless gyrator-capacitor (gC) multiport network as a prototype circuit, both for analysis and synthesis filter banks in FI ADC, is an implementation of the strategy to design filters with low sensitivity to parameter changes. An additional advantage is designing the synthesis filter as stable infinite impulse response (IIR) instead of commonly used finite impulse response (FIR) filters. It provides several dozen-fold saving in the number of applied multipliers.. The analysis and synthesis filters in FI ADC are implemented as filter pairs. An additional example of three-filter bank demonstrates versatility of NANO-studio software.

The Spectra of Filters

2021 ◽  
pp. 204-268
Author(s):  
Victor Lazzarini
Keyword(s):  
Fourier Transform ◽  
Impulse Response ◽  
Discrete Time ◽  
Filter Design ◽  
Finite Impulse Response ◽  
Infinite Impulse Response ◽  
Main Body ◽  
Analysis Tool ◽  
The Fourier Transform ◽  
Definition Of

This chapter now turns to the discussion of filters, which extend the notion of spectrum beyond signals into the processes themselves. A gentle introduction to the concept of delaying signals, aided by yet another variant of the Fourier transform, the discrete-time Fourier transform, allows the operation of filters to be dissected. Another analysis tool, in the form of the z-transform, is brought to the fore as a complex-valued version of the discrete-time Fourier transform. A study of the characteristics of filters, introducing the notion of zeros and poles, as well as finite impulse response (FIR) and infinite impulse response (IIR) forms, composes the main body of the text. This is complemented by a discussion of filter design and applications, including ideas related to time-varying filters. The chapter conclusion expands once more the definition of spectrum.

scholarly journals A Proportionate Normalized Maximum Correntropy Criterion Algorithm with Correntropy Induced Metric Constraint for Identifying Sparse Systems

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 683 ◽  
Author(s):  
Yingsong Li ◽  
Yanyan Wang ◽  
Laijun Sun
Keyword(s):  
Impulse Response ◽  
Adaptive Filter ◽  
Finite Impulse Response ◽  
Least Mean Square ◽  
Sparse Systems ◽  
Simulation Results ◽  
Maximum Correntropy Criterion ◽  
Non Gaussian ◽  
Fir Systems ◽  
Filter Algorithms

A proportionate-type normalized maximum correntropy criterion (PNMCC) with a correntropy induced metric (CIM) zero attraction terms is presented, whose performance is also discussed for identifying sparse systems. The proposed sparse algorithms utilize the advantage of proportionate schemed adaptive filter, maximum correntropy criterion (MCC) algorithm, and zero attraction theory. The CIM scheme is incorporated into the basic MCC to further utilize the sparsity of inherent sparse systems, resulting in the name of the CIM-PNMCC algorithm. The derivation of the CIM-PNMCC is given. The proposed algorithms are used for evaluating the sparse systems in a non-Gaussian environment and the simulation results show that the expanded normalized maximum correntropy criterion (NMCC) adaptive filter algorithms achieve better performance than those of the squared proportionate algorithms such as proportionate normalized least mean square (PNLMS) algorithm. The proposed algorithm can be used for estimating finite impulse response (FIR) systems with symmetric impulse response to prevent the phase distortion in communication system.

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