Model reduction of discrete bilinear systems
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Model reduction of discrete bilinear systems by Christopher A. Crawley

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Published .
Written in English


  • Control theory.,
  • System analysis.

Book details:

Edition Notes

Statementby Christopher A. Crawley.
The Physical Object
Paginationvii, 62 leaves, bound :
Number of Pages62
ID Numbers
Open LibraryOL16563547M

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(). Generalised tangential interpolation for model reduction of discrete-time MIMO bilinear systems. International Journal of Control: Vol. 84, No. 8, pp. Cited by: examples and compared with the method of balanced truncation for bilinear systems. Keywords: model order reduction, bilinear systems, tangential interpolation, discrete systems 1 Introduction Nowadays many technical and industrial processes require accurate and systematic analysis and simulation with the help of mathematical models. [2] C. Hwang and C. Hsieh,’Order reduction of discrete time system via Bilinear Routh approximation’, ASME, , Meas, Control, , Vol ,p [3] G.V.K.R Sastry, G. Lakshmi Narayanaet. al “Particle Swarm Optimization technique for Model reduction of High-Order Discrete Time Systems”, . A Krylov subspace based projection method is presented for model reduction of large scale bilinear systems. A reduced bilinear system is constructed in such a way that it matches a desired number of moments of multivariable transfer functions corresponding to the kernels of Volterra series representation of the original system.

  A bilinear Schwarz approximation method has been proposed in the literature for reducing the order of discrete-time systems. The reduced model derived by the method preserves the stability and first few time-moments of the original one.   An optimal model reduction method is presented to obtain stable reduced-order models for discrete-time descriptor systems. A parametrization based on the bilinear Routh approximation of linear normal discrete-time systems is used to parametrize the causal subsystems of .   This paper presents a novel method for identification of discrete-time, time-invariant state-space models of bilinear dynamical systems using the steady-state portion of a single input/multiple output time-history measurements. These measurements are recorded by exciting the system with a linear combination of sine and cosine functions of user-selected frequencies enriched . C. S. Hsieh & C. Hwang, Model reduction of linear discrete time systems using bilinear schwarz approximations, International Journal of System Science, 21(1), , Google Scholar Cross Ref.

In this article, we discuss a model order reduction method for multiple-input and multiple-output discrete-time bilinear control systems. Similar to the continuous-time case, we will show that a. A model reduction scheme of k-power bilinear systems is proposed in this work. The canonical state space structure of k-power systems is used to simplify a balancing like model reduction scheme. A new method without stability limitation is proposed for model order reduction of discrete-time linear time-invariant systems. By using bilinear transformation between discrete-time systems and continuous-time systems, a continuous-time model-order reduction method is extended to discrete-time systems.   In this paper, we extend this method to bilinear systems, and present a time domain model order reduction method for MIMO bilinear systems. This approach expands the state variables in the space spanned by general orthogonal polynomials, then the expansion coefficient vectors are calculated by a recurrence formula.