Efficient algorithm for optimal model reduction

Myo Taeg Lim, N. N. Puri

Research output: Contribution to journalArticle

Abstract

In this paper we present a new algorithm for obtaining the optimal approximation of high-order linear continuous time systems. The reduced-order model is determined by a recursive optimization procedure which minimizes a positive definite function of the integral impulse response error between the full and reduced-order model. The proposed optimization algorithm involving the performance index of the complicated nonlinear type is formulated in terms of linear equations which can be easily solved in a recursive manner. By introducing a Routh table and its reverse elimination procedure for solving the linear equations, the computational efficiency is greatly improved.

Original languageEnglish
Pages (from-to)374-383
Number of pages10
JournalInternational Journal of Modelling and Simulation
Volume19
Issue number4
Publication statusPublished - 1999 Dec 1

Fingerprint

Reduced Order Model
Model Reduction
Linear equations
Linear equation
Efficient Algorithms
Positive Definite Functions
Continuous time systems
Optimal Approximation
Continuous-time Systems
Impulse Response
Performance Index
Computational efficiency
Impulse response
Computational Efficiency
Elimination
Linear Time
Reverse
Optimization Algorithm
Table
Linear Systems

ASJC Scopus subject areas

  • Hardware and Architecture
  • Modelling and Simulation
  • Software
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety

Cite this

Efficient algorithm for optimal model reduction. / Lim, Myo Taeg; Puri, N. N.

In: International Journal of Modelling and Simulation, Vol. 19, No. 4, 01.12.1999, p. 374-383.

Research output: Contribution to journalArticle

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