Application of infinite dimensional linear programming to IIR filter design with time domain constraints

AbstractIn the field of Model-Driven Engineering, Triple Graph Grammars (TGGs) play an important role as a rule-based means of implementing consistency management. From a declarative specification of a consistency relation, several operations including forward and backward transformations, (concurrent) synchronisation, and consistency checks can be automatically derived. For TGGs to be applicable in realistic application scenarios, expressiveness in terms of supported language features is very important. A TGG tool is schema compliant if it can take domain constraints, such as multiplicity constraints in a meta-model, into account when performing consistency management tasks. To guarantee schema compliance, most TGG tools allow application conditions to be attached as necessary to relevant rules. This strategy is problematic for at least two reasons: First, ensuring compliance to a sufficiently expressive schema for all previously mentioned derived operations is still an open challenge; to the best of our knowledge, all existing TGG tools only support a very restricted subset of application conditions. Second, it is conceptually demanding for the user to indirectly specify domain constraints as application conditions, especially because this has to be completely revisited every time the TGG or domain constraint is changed. While domain constraints can in theory be automatically transformed to obtain the required set of application conditions, this has only been successfully transferred to TGGs for a very limited subset of domain constraints. To address these limitations, this paper proposes a search-based strategy for achieving schema compliance. We show that all correctness and completeness properties, previously proven in a setting without domain constraints, still hold when schema compliance is to be additionally guaranteed. An implementation and experimental evaluation are provided to support our claim of practical applicability.

Download Full-text

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

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189778 ◽

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.

Download Full-text

Time-Domain Matrix Analysis of Polyphase FIR Filters

International Journal of Electrical Engineering Education ◽

10.7227/ijeee.49.3.7 ◽

2012 ◽

Vol 49 (3) ◽

pp. 275-290

Author(s):

Eric J. Balster ◽

Francis D. Fradette ◽

Frank A. Scarpino ◽

Kerry L. Hill

Keyword(s):

Time Domain ◽

Filter Design ◽

Digital Signal ◽

Time Domain Analysis ◽

Discrete Systems ◽

Domain Analysis ◽

Matrix Analysis ◽

Student Survey ◽

Z Domain ◽

Polyphase Filters

Polyphase filter design is a common subject studied in discrete systems analysis and digital signal processing (DSP) courses. However, the classic z-domain analysis, utilizing the noble identities, gives a conclusion to the true physical structures of polyphase filters which may not be obvious to many students. The proposed time-domain analysis provides a more straightforward development of polyphase implementation of interpolation and decimation functions, and hopes to provide students with a more visual representation of the polyphase interpolation and decimation processes. Results from a student survey show that over 73% of students believe that the proposed polyphase analysis strengthened their understanding of polyphase filters, and over 71% would prefer to use the proposed method over the traditional z-domain analysis when explaining polyphase filters to others.

Download Full-text

An avoidance of premature convergence in IIR filter design using PSO

2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference ◽

10.1109/apsipa.2013.6694375 ◽

2013 ◽

Author(s):

Yuji Nishimura ◽

Kenji Suyama

Keyword(s):

Filter Design ◽

Premature Convergence ◽

Iir Filter

Download Full-text

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

Journal of Vibration and Control ◽

10.1177/1077546316657502 ◽

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.

Download Full-text