Hybrid method of reduced order modelling for LTI system using evolutionary algorithm

Sikander, Afzal; Thakur, Padmanabh; Uniyal, Ishita

doi:10.1109/ngct.2016.7877394

Cited by 8 publications

(3 citation statements)

References 15 publications

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“…For simplicity, such singular values (SV) are generally ordered downward to truncate states that match smaller Hankel singular values as follows Rowley, 2005;Athanasios C, 2011a;Afzal Sikander et al, 2017;Maury, 2017). • This is also a significant action of the minimality of realization of the original system is the diminishing positive number such that…”

Section: Balanced Realization (Br) Methodsmentioning

confidence: 99%

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Higher-Order Reduction of Linear System and Design of Controller

Suman¹

2020

SJKFU

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In this, a new Higher-Order Reduction (HOR) scheme is proposed for better understanding and explanation of a large-scale dynamical (LSD) system. This proposed scheme is based on a balanced realization method (BRM) in which the steady-state gain issue of the BRM is circumvented. This method guarantees that the system is stable and preserved static behaviour. The reduced-order model (ROM) is calculated to maintain entire parameters with fair accuracy by model order reduction (MOR). Further, in terms of transient and frequency responses, the performance of the proposed scheme is analysed. In this paper, we have used two approaches that are balanced realization method (BRM) and stability equation method (SEM) for HOR. According to that procedure, the denominator coefficients (DC) of the reduced model is obtained by BRM and the numerator coefficients (NC) are computed by SEM. This technique gives the least performance error indices compared to some another existing approaches through a literature review. Additionally, the control action is obtained by using the genetic algorithm (GA) based PID (proportional integral derivative) controller has been proposed. In this tuning optimized PID parameters done using of objective functions, the concept of error minimisation (performance index). As the proposed approach is used both in the simplification of systems and in the design of controller, therefore it may be applied in various applications of LSD system analysis and design. The proposed scheme is proved by a numerical example. ‫العلوم‬ ‫فرع‬ ‫فيصل،‬ ‫امللك‬ ‫لجامعة‬ ‫العلمية‬ ‫املجلة‬ ‫والطبيعية‬ ‫األساسية‬ ، ‫الطباعة)‬ ‫(بانتظار‬ ‫العدد‬ ‫الطباعة)،‬ ‫(بانتظار‬ ‫املجلد‬

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Section: Balanced Realization (Br) Methodsmentioning

confidence: 99%

“…() gt is the impulse response of the system. these error indices are described in (Narwal et al, 2016;Afzal Sikander et al, 2018;Afzal Sikander et al, 2017;Afzal Sikander et al, 2015c; as follows…”

Section: Gs Rmentioning

confidence: 99%

Higher-Order Reduction of Linear System and Design of Controller

Suman¹

2020

SJKFU

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“…Further, the hybridization of genetic algorithm and CS approach is proposed to make a balance between exploration and exploitation ability [38]. Furthermore, modified cuckoo search (MCS) is also applied in MOR field [39][40][41]. The meta-heuristic approaches have strongly proved their capability and effectiveness in MOR field.…”

Section: Introductionmentioning

confidence: 99%

A meta-heuristic cuckoo search and eigen permutation approach for model order reduction

2018

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In this paper, a new model order reduction technique is presented by combining the benefits of the meta-heuristic cuckoo search optimization and Eigen permutation methods for order reduction of higher order continuous-time systems. In the proposed approach, the numerator and the denominator polynomials of reduced order model are determined by Cuckoo search and Eigen permutation approaches, respectively. The proposed approach preserves the stability of the original system into the lower order model as the Eigen permutation retains the dominant pole with simultaneous cluster formation of the remaining real and complex poles. The effectiveness of the proposed method is validated by single-input single-output and multiple-inputs multipleoutputs numerical examples.

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Linear System of Order Reduction Using a Modified Balanced Truncation Method

Suman

Kumar

2021

Circuits Syst Signal Process

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Hybrid method of reduced order modelling for LTI system using evolutionary algorithm

Cited by 8 publications

References 15 publications

Higher-Order Reduction of Linear System and Design of Controller

Higher-Order Reduction of Linear System and Design of Controller

A meta-heuristic cuckoo search and eigen permutation approach for model order reduction

Linear System of Order Reduction Using a Modified Balanced Truncation Method

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