Direct truncation method for order reduction of discrete interval system

Choudhary, Amit Kumar; Nagar, Shyam Krishna

doi:10.1109/indcon.2013.6726040

Cited by 22 publications

(9 citation statements)

References 20 publications

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“…Example 1: Consider third-order uncertain system available from literature (Choudhary & Nagar, 2013a, 2013bIsmail et al, 1997) as The computed error J, through different Cases, is made known in Table 10 offering the support to Case 2 for calculating minimum error when compared to the existing techniques. The next section explains the limitation encountered during the error computation.…”

Section: Illustrative Examplesmentioning

confidence: 99%

“…To accept the arrangement's rational acceptability, Case 2 is applied to the real-time system through the example below. (Ismail et al, 1997) 0.1398 0.0195 0.1810 0.0741 Direct truncation (Choudhary & Nagar, 2013a) 2.1491 2.7778 0.0278 0.0077 Gamma-Delta Appr. (Choudhary & Nagar, 2013b) 0.0157 0.0035 0.1292 0.0250 Note: The Proposed Case 2 present an appropriate acceptance as compared to rest of the algorithms.…”

Section: Illustrative Examplesmentioning

confidence: 99%

“…(Ismail et al, 1997) 0.1398 0.0195 0.1810 0.0741 Direct truncation (Choudhary & Nagar, 2013a) 2.1491 2.7778 0.0278 0.0077 Gamma-Delta Appr. (Choudhary & Nagar, 2013b) 0.0157 0.0035 0.1292 0.0250 Note: The Proposed Case 2 present an appropriate acceptance as compared to rest of the algorithms. By the proposed algorithm cases, the reduced-order model is obtained as Case 1: Table 10 depicts the error for first-and second-order reduced models through the discussed four Cases and other prevailing techniques for Example 1.…”

Section: Illustrative Examplesmentioning

confidence: 99%

“…Dolgin and Zeheb (2004) states the demand of assuming the required order polynomial coefficients at an earlier stage, for computation of error between the polygons in the complex plane (original uncertain system) and the point representing the resulted reduced-order fixed-coefficients systems for deriving the reduced-order model. In recent times, algorithms that expressed their advancement from deterministic systems to uncertain systems are work by Choudhary and Nagar (2013a, 2013b, 2015b, namely direct truncation, gamma-delta approximation and Routh-Pade approximation. Freshly, the article (Choudhary & Nagar, 2015a) offers the application of existing algorithms to power systems components.…”

Section: Introductionmentioning

confidence: 99%

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Novel arrangement of Routh array for order reduction of z-domain uncertain system

Choudhary

Nagar

2017

Systems Science & Control Engineering

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This paper presents a novel arrangement of Routh table array for deriving an approximate model of a higher order z-domain uncertain system. The demand for this computation is to procure a lower order model which is easy to be exercised in comparison to their original large scale systems. Additionally, the derived model should preserve fewer dynamic characteristic of the comprehensive higher order systems. The mentioned new arrangement is achieved from the arena of different combinations of numerator and denominator polynomials. The combinations are validated by their practice over the conventional example from the literature. This precise blend is then applied to a real-time system for its rational acceptability. Both the models play a significant role in establishing the algorithm. Besides this, the limitation encountered during the foundation course of the arrangement is also taken into consideration. The paper also offers a future scope for fellow researchers.

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Section: Illustrative Examplesmentioning

confidence: 99%

Section: Illustrative Examplesmentioning

confidence: 99%

Section: Illustrative Examplesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Novel arrangement of Routh array for order reduction of z-domain uncertain system

Choudhary

Nagar

2017

Systems Science & Control Engineering

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“…In literature [2], [17]- [20], several methods are also available for DIS. Some of the methods in this category are direct series and dominant pole retention [2], Padé and multipoint Padé approximation [17], [18], Gamma-delta approximation [19], etc. The prospective two new approaches of order diminution for DISs are differentiation calculus [21] and Mikhailov stability criterion [20].…”

Section: Introductionmentioning

confidence: 99%

Model Order Diminution of Discrete Interval Systems Using Kharitonov Polynomials

et al. 2022

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In this research proposal, diminution of higher order (HO) discrete interval system (DIS) is accomplished by utilizing Kharitonov polynomials. The DIS is firstly, transformed into continuous interval system (CIS). The Markov-parameters (MPs) and time-moments (TMs) are exploited for determination of approximated models. The ascertainment of model order diminution (MOD) of DISs is done by Routh-Padé approximation. The Routh table is utilized to obtain the denominator of approximated model. The unknown numerator coefficients of desired approximated model are determined by matching MPs and TMs of DISs and desired model. This whole procedure of MOD is elucidated with the help of one test illustration in which third order system is reduced to first order model as well as second order model. To prove applicability of the proposed method, impulse, step and Bode responses are plotted for both system and model. For relative comparison, time-domain specifications of proposed model are tabulated for both upper and lower limits. Further, performance indices are specified for dissimilarities between responses of system and model. The obtained results depict the effectiveness and efficacy for the proposed method.

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