Approximation and optimization of discrete systems using order reduction technique

Ramesh, K.; Ganesan, R.; Mahalakshmi, K.

doi:10.1016/j.egypro.2017.05.192

Cited by 10 publications

(2 citation statements)

References 13 publications

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“…Yu and Xiong [8] studies an H∞ model reduction problem for interval frequency negative imaginary systems. Ramesh et al [9] propose that the higher-order discrete systems are approximated into the lower-order discrete systems with the help of proposed model order reduction technique. is order reduction includes cross multiplication of polynomials process and using the Genetic Algorithm at the tail end of approximation process.…”

Section: Introductionmentioning

confidence: 99%

FIR to FIR Model Reduction with Linear Group Delay in Passband by SDP Optimization

Song

Zhang

2020

Journal of Electrical and Computer Engineering

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Filter model reduction is an important optimization method in digital signal processing. A method of FIR to FIR model reduction using SDP optimization is proposed in this paper. At first, we use SDP to design an original FIR filter. Then we name a general K-order FIR digital filter H1z−1 with coefficient values equal to the first K + 1 filter coefficient values of H0z−1. Finally, we design a new general K-order FIR digital filter H2z−1 connected in parallel with H1z−1 using SDP optimization. The experiment results show this method has good performance on the magnitude error and the linear phase in passband. Therefore, this method can be used in the field of digital signal processing.

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Section: Introductionmentioning

confidence: 99%

FIR to FIR Model Reduction with Linear Group Delay in Passband by SDP Optimization

Song

Zhang

2020

Journal of Electrical and Computer Engineering

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“…In this paper, scheme for the higher order reduction of discrete time systems using Padé approximation and modified pole clustering technique has been proposed (Bistritz and Shaked, 1984;Vishwakarma and Prasad, 2008). By applying linear transformation the original discrete time system is changed to continuous time system and the reduced order model is derivative of the original system by using the above stated techniques which imitates the behaviour of the original one (Ramesh, et al, 2017). Finally, result of the inverse transformation of the derivative of the continuous original system produces reduced order model in discrete time system.…”

Section: Introductionmentioning

confidence: 99%

Dominant Pole Based Approximation for Discrete Time System

Richa

Kumar

2019

Int J Math, Eng, Manag Sci

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This paper presents an effective procedure for model order reduction of discrete time control system. The exact model derived from complex dynamic systems proves to be very complicated for analysis, control and design. This necessity brings about using a tool known as model order reduction technique or model simplification. A novel mixed method has been implemented in this paper for reducing the order of the large scale dynamic discrete system. Dominant pole based pole clustering method has been used to derive the coefficients of denominator polynomial while Padé approximation has been applied to obtain the coefficients of numerator polynomial of the reduced order model. The proposed method is quite simple and able to generate a stable reduced order model from high order stable discrete systems. The dominancy of poles has been decided by values of the ratio of residue to its pole. The pole is considered dominant which have larger ratio value. An illustrative example has been considered to show the various reduction steps. The result obtained confirms the effectiveness of the approach.

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