ARSTRACT : A simple method is proposed for order reduction of linear continuous systems with real distinct eigenvalues. The steady state parts qf the unit step responses of the original and reduced-order models are matched in this method. Zeros are synthesized by minimizing the error between the tra
Reduced order modelling of linear multivariable systems using an error minimization technique
β Scribed by S. Mukherjee; R.N. Mishra
- Publisher
- Elsevier Science
- Year
- 1988
- Tongue
- English
- Weight
- 425 KB
- Volume
- 325
- Category
- Article
- ISSN
- 0016-0032
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β¦ Synopsis
The method of' reducing the order of's linear multir~ariablr system is discussrd. The dominant poles of the original system are retainc~d,.f~llor~c?d by matching the steady state parts of the unit step responses qf' the original and reduced systems. Each element of' the tran.sfkr Junction matri.x (?f' the originul system is considered separately. E coqjficients of the numerator pol_vnomials qf the elements qf the reduced order .system transfer .fimction matri.x are then determined by minimizing the Integral Square Error (ISE) between the transient parts of the unit step reponses. An example illustrates the method and the result is compared to another method.
π SIMILAR VOLUMES
For monovariable systems, if the nominal transfer function is irreducible the minimal order is tlw clqwr of'tllr(/~~tl(~l~litl~ltot.~)ol!'l~ol~liCtl. In multivariable systems. this order is (I/ krst equal to the degree of the last common multiple of the denominators of the transfer matrix function e
This paper proposes reduced-order estimation technique by the recursive least-squares filter and fixed-point smoother in linear discrete-time systems, given output measurement data. The estimators require the information of the system matrix, the observation vector of the signal generating model and