Optimal Hankel norm model reduction for discrete-time descriptor systems

Cao, Xingang; Saltik, M.B.; Weiland, S.

doi:10.1016/j.jfranklin.2018.11.047

Cited by 12 publications

(10 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, the steady-state matching of the actual system with its reduced order representation fails most of the time. They are furthermore hampered as the typical highfrequency ranges have poor precision and may have non-minimal phase characteristics (Cao, Saltik et al, 2019;Benner, Gugercin et al, 2015). Further the reduction method application to many researchers such as (J.…”

Section: Introductionmentioning

confidence: 99%

Higher-Order Reduction of Linear System and Design of Controller

Suman¹

2020

SJKFU

View full text Add to dashboard Cite

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

show abstract

Section: Introductionmentioning

confidence: 99%

Higher-Order Reduction of Linear System and Design of Controller

Suman¹

2020

SJKFU

View full text Add to dashboard Cite

show abstract

“…The MOR is numerical method for order Decrease of large -scale system to enhance the simulation with a suitably easy system, which captures the main characteristics of the original character one, which reduces the complication of the original large-scale system and produces a ROM (reduced-order model) to characterize the original one [13].in this present basically three MOR (model order reduction) methods, however, there may be no technique that gives the quality consequences for all of the structures [14]. So, each system makes use of the quality approach in keeping with its application.…”

Section: Introductionmentioning

confidence: 99%

Model Order Reduction of Transmission Line Model

Suman

Kumar

2020

Wseas Transactions on Circuits and Systems

View full text Add to dashboard Cite

Transmission Line model are an important role in the electrical power supply. Modeling of such system remains a challenge for simulations are necessary for designing and controlling modern power systems.In order to analyze the numerical approach for a benchmark collection Comprehensive of some needful real-world examples, which can be utilized to evaluate and compare mathematical approaches for model reduction. The approach is based on retaining the dominant modes of the system and truncation comparatively the less significant once.as the reduced order model has been derived from retaining the dominate modes of the large-scale stable system, the reduction preserves the stability. The strong demerit of the many MOR methods is that, the steady state values of the reduced order model does not match with the higher order systems. This drawback has been try to eliminated through the Different MOR method using sssMOR tools. This makes it possible for a new assessment of the error system Offered that the Observability Gramian of the original system has as soon as been thought about, an H∞ and H2 error bound can be calculated with minimal numerical effort for any minimized model attributable to The reduced order model (ROM) of a large-scale dynamical system is essential to effortlessness the study of the system utilizing approximation Algorithms. The response evaluation is considered in terms of response constraints and graphical assessments. the application of Approximation methods is offered for arising ROM of the large-scale LTI systems which consist of benchmark problems. The time response of approximated system, assessed by the proposed method, is also shown which is excellent matching of the response of original system when compared to the response of other existing approaches .

show abstract

“…The other drawbacks are the low precision in average ranges as well as high frequency and the non-minimum phase characteristics. (Benner et al, 2015;Cao et al, 2019). Based upon the dominant poles method, numerous mixed methods have been suggested by (Singh et al, 2016), The continued method and time matching fraction expansion can produce stable systems models.…”

Section: Introductionmentioning

confidence: 99%

Model Order Reduction by Using Improved Approximation Techniques

Suman¹,

Kumar²

2020

SJKFU

View full text Add to dashboard Cite

A simplified approach for model order reduction (MOR) is presented in this article using the balanced singular perturbation approximation (BSPA) approach applicable to large-scale linear dynamical (LSLD) systems. The reduced system was so designed to preserve complete parameters of the original system with reasonable accuracy, employing MOR. The approach is based on the retention of the dominant states of the system and comparatively less important once. The reduced system comes from the preservation of the dominant States (say "desirable states") of the original system and thus from stability to preservation. The key demerit of the Balanced Truncation approach is that the ROM steady-state values do not correspond with the higher-order systems. This drawback has been eliminated in the proposed approach, which leads to hybridization of balanced truncation and singular perturbation approximation into a novel reduction method without the loss of retaining its dynamic behaviour. The proposed approach has been tested on LSLD systems and the results obtained show the efficacy of the approach. The methodology presented has been tested on two typical numerical examples taken from the literature review, to examine the performance, precision and comparison with other available standard order reduction methods. both the quality and the presentation of the manuscript. I would like to thank my supervisor, Dr. Awadhesh Kumar, for the patience guidance, encouragement and advice, he has provided throughout my time as his student. I have been extremely lucky to have a supervisor who cared so much about my work and who responded to my questions and queries so promptly.

show abstract

Optimal Hankel norm model reduction for discrete-time descriptor systems

Cited by 12 publications

References 33 publications

Higher-Order Reduction of Linear System and Design of Controller

Higher-Order Reduction of Linear System and Design of Controller

Model Order Reduction of Transmission Line Model

Model Order Reduction by Using Improved Approximation Techniques

Contact Info

Product

Resources

About