Suboptimal Control Using Model Order Reduction

Pati, Avadh; Kumar, Awadhesh; Chandra, Dinesh

doi:10.1155/2014/797581

Cited by 19 publications

(4 citation statements)

References 5 publications

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“…25), Proposed ROM using RSA and SE (Eq. 28), MOR in literature such as GA-MOR [29], Conv-MOR [30] and BBBC-MOR [31] The purpose of comparison is to compare the proposed technique with original to prove similarity of characteristic. These reduced models are also compared with reduced models in literature and found equally good even better in some cases.…”

Section: Resultsmentioning

confidence: 99%

Model Order Reduction by Routh Stability Array with Stability Equation Method for SISO and MIMO Systems

Sambariya¹,

Rajawat²

2016

ujes

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In this paper, the technique applicable to reduce a high-order system to a low-order system is presented. The methods used are Routh stability array (RSA) method and stability equation (SE) method to get the reduced model of systems. The application of the techniques is examined over SISO linear time invariant systems and extended to MIMO systems. The step response performance of the reduced models gets compared to the original system as well as reduced models in literature in terms of rise-time, settling-time, peak-time and peak of the system. The comparative study reveals that the performances of the reduced models using proposed RSA and SE methods are encouraging as compared to that of with reduced models in literature.

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Section: Resultsmentioning

confidence: 99%

Model Order Reduction by Routh Stability Array with Stability Equation Method for SISO and MIMO Systems

Sambariya¹,

Rajawat²

2016

ujes

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“…A second order reduced model can be obtained by considering above assumptions and solving the following equations. Using (6)-(10), variable for reduced order model (12) can be obtained as [20],…”

Section: Model Order Reduction Proceduresmentioning

confidence: 99%

“…A performance comparison of proposed method with other well known existing methods is provided in Table I. This performance comparison is made on the basis of an error index which is known as Integral Square Error(ISE) [20][21] is mentioned in the Table I. This integral square error(ISE) is an error between the transient part of the original higher order model and the reduced order model.…”

Section: Model Order Reduction Proceduresmentioning

confidence: 99%

Eigen spectrum based moment matching technique for model order reduction

Lavania

Nagaria

2015

2015 39th National Systems Conference (NSC)

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In this paper a mixed approach for model order reduction is proposed. The proposed approach combines eigen spectrum analysis and Padé based moment matching technique for model order reduction. The denominator of the higher order system(HOS) is derived using eigen spectrum analysis whereas numerator dynamics are determined using Padé based moment matching technique which utilizes both time moment and Markov parameters. The efficiency and powerfulness of the method is evaluated in terms of a performance index which is known as integral square error(ISE). This method guarantees stability if the original system is stable. I. INTRODUCTIONIn the analysis of complex and intricate systems, it is often required to simplify the system for the ease of analysis, simulation and implementation. When mathematical description of any higher order system (HOS) is presented, several considerations and assumptions are made. Moreover, consideration of all aspects would make the mathematical description of the system more complex to analyze. This has preceded model order reduction (MOR) a necessary tool. Concept behind the model order reduction is to replace the higher order system with an approximated system, which provides ease of simulation, analysis and better control. Further, such a system has reduced dimensions, which significantly reduces the simulation and design time. Additionally it must be ascertained that the characteristics of the reduced order system remain pristine. The area of model order reduction is very vast and has always attracted researchers to extend the previous literature or to propose new methods. Model order reduction has been broadly classified in two domains i.e. Time domain and Frequency domain. A wide variety of techniques have been proposed in both the domains of model order reduction [1][2][3][4][5]. In time domain Singular method,Modal method,Optimal Solution etc. have been proposed [5][6][7][8][9][10]. Whereas, in frequency domain Padé approximation, Routh Approximation, Continued Fraction etc. have been proposed [11][12][13][14].

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“…It also included fourth order example and reduced to 2nd order model. Pati at el have proposed work on sub-optimal control using model order reduction [15]. Lodhwal and Jha, have proposed the performance comparison of different type of reduced order modeling methods [16,17].…”

Section: Introductionmentioning

confidence: 99%

Reduced Order Model of Single Machine Infinite Bus Power System Using Stability Equation Method and Self-adaptive Bat Algorithm

Sambariya¹,

Arvind²

2016

ujca

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In this paper, a largeorder system is reduced by using the self adaptive bat algorithm (SABA) to a reduced-order approximation. The numerator coefficients of a desired reduced-order system are optimized based on integral square error minimization as an objective function pertaining to a unit-step as input. The denominator of the reduced order model is solved by stability equation method. The efficacy of the proposed method is tested with SMIB test systems to get a corresponding reduced-order system. The results are satisfactory in terms of minimum error with the proposed method as compared to Routh approximation and Stability equation based reduced models.

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Suboptimal Control Using Model Order Reduction

Cited by 19 publications

References 5 publications

Model Order Reduction by Routh Stability Array with Stability Equation Method for SISO and MIMO Systems

Model Order Reduction by Routh Stability Array with Stability Equation Method for SISO and MIMO Systems

Eigen spectrum based moment matching technique for model order reduction

Reduced Order Model of Single Machine Infinite Bus Power System Using Stability Equation Method and Self-adaptive Bat Algorithm

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