On Chuang's continued fraction method of model reduction

Khatwani, K.; Tiwari, Rajesh Kumar; Bajwa, Joginder S.

doi:10.1109/tac.1980.1102437

Cited by 26 publications

(3 citation statements)

References 9 publications

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“…Samson 1982) and have found applications in identification (Robins and Wellstead 1981, Gauvrit et al 1981). The MCF approaches have been used to simplify model order in the approximation of transfer functions (Garg and Singh 1981, Pal 1980, Khatwani et al, 1980, Hwang and Shih 1982. First the covariance propagation problem will be formulated into a MCF framework and then a numerical comparison will be conducted between this method and conventional methods.…”

Section: Introductionmentioning

confidence: 99%

An implementation method for the discrete Kalman filter with applications to large-scale systems

Repperger

1984

International Journal of Control

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An interesting implementation procedure is developed for use in a covariance propagation problem involving a discrete Kalman filter. Using a matrix continued fraction (!\olCF) method for the calculation of the covariance matrix, the final irnplementation requires one matrix inversion involving a sequence of controllability matrices, observability matrices, and an initial condition matrix. Using procedures as discussed by Mendel (1971), Bierman (1973, 1977(1971) and Carlson (1973), a numerical comparison in terms of computing timo and computer storage is made between the approach developed here and the conventional method.This algorithm is intended to be used as an alternative method to implement the Kalman filter. For certain classes of large-scale systems, the MCF method provides both a reduction of computer time and computer storage. An example is worked to illustrate the applicability of the approach presented here.

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Section: Introductionmentioning

confidence: 99%

An implementation method for the discrete Kalman filter with applications to large-scale systems

Repperger

1984

International Journal of Control

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“…1980),the Stieltjes form Tiwari 1978, Khatwani et al 1976), the Jordan form (Hwang and Shih 1984), and the biased Cauer form about s = 0 and s = 00 (Hwang and Guo 1985).…”

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confidence: 99%

“…Following the procedure given by Lamba and Rao (1978), an approximate relationship between the state vector x of the original system and the state vector 2 of the red uced model can be constructed as follows where 2", NPx~Max…”

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confidence: 99%