IIR Filter Design

1998 ◽  
pp. 152-192
Author(s):  
S.M. BOZIC ◽  
R.J. CHANCE
Keyword(s):  
Filter Design ◽  
Iir Filter

Control loop oscillation detection and quantification using PRONY method of IIR filter design and deep neural network

2021 ◽  
pp. 1-14
Author(s):  
Sachin Sharma ◽  
Vineet Kumar ◽  
K.P.S. Rana
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Filter Design ◽  
Support Vector ◽  
Control Loop ◽  
External Interference ◽  
Iir Filter ◽  
Prony Method ◽  
Oscillation Detection ◽  
Detection And Quantification

Generally, the process industry is affected by unwanted fluctuations in control loops arising due to external interference, components with inherent nonlinearities or aggressively tuned controllers. These oscillations lead to production of substandard products and thus affect the overall profitability of a plant. Hence, timely detection of oscillations is desired for ensuring safety and profitability of the plant. In order to achieve this, a control loop oscillation detection and quantification algorithm using Prony method of infinite impulse response (IIR) filter design and deep neural network (DNN) has been presented in this work. Denominator polynomial coefficients of the obtained IIR filter using Prony method were used as the feature vector for DNN. Further, DNN is used to confirm the existence of oscillations in the process control loop data. Furthermore, amplitude and frequency of oscillations are also estimated with the help of cross-correlation values, computed between the original signal and estimated error signal. Experimental results confirm that the presented algorithm is capable of detecting the presence of single or multiple oscillations in the control loop data. The proposed algorithm is also able to estimate the frequency and amplitude of detected oscillations with high accuracy. The Proposed method is also compared with support vector machine (SVM) and empirical mode decomposition (EMD) based approach and it is found that proposed method is faster and more accurate than the later.

scholarly journals Analysis of half-band approximately linear phase IIR filter realization structure in MATLAB

2015 ◽  
Vol 28 (4) ◽  
pp. 611-623 ◽  
Author(s):  
Aleksandar Radonjic ◽  
Jelena Certic
Keyword(s):  
Fixed Point ◽  
Detailed Analysis ◽  
Filter Design ◽  
Linear Phase ◽  
Parallel Connection ◽  
Iir Filter ◽  
Filter Structure ◽  
Band Filter ◽  
Design Algorithms

In this paper a detailed analysis of an atypical filter structure in MATLAB Filter Design and Analysis (FDA) Tool is presented. As an example of atypical filter structure, the IIR half-band filter with approximately linear phase realized as a parallel connection of two all-pass branches was examined. We compare two types of those filters obtained by two different design algorithms. FDA tool was used for the experiment because different effects of the fixed point implementation can be simulated easily. One of the goals of this paper was to compare results obtained by two different design algorithms. In addition, different realizations of the filter structure based on the parallel connection of two all-pass branches were examined.

Efficient Multirate Filtering

2002 ◽  
pp. 105-142 ◽  
Author(s):  
Ljiljana D. Milic ◽  
Miroslav D. Lutovac
Keyword(s):  
Digital Filter ◽  
Filter Design ◽  
Narrow Band ◽  
Sampling Rate ◽  
Wide Band ◽  
Digital Filter Design ◽  
Iir Filter ◽  
Design And Implementation ◽  
Sampling Rate Conversion ◽  
Rate Conversion

Application of multirate techniques to improve digital filter design and implementation are considered in this chapter. FIR and IIR filter design and implementation for sampling rate conversion by integer and rational factors are presented. Sharp narrow-band and wide-band multirate design techniques are discussed. Accurate designs of FIR and IIR half-band filters are described in detail. Several examples are provided to illustrate the multirate approach to filter design.

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