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Multivariant Active Systems

Automation and Remote Control, 2001
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Avdeev, V. P., Kiseleva, T. V., Burkov, V. N.   +2 more
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The multivariable nature of multivariable feedback systems

The 22nd IEEE Conference on Decision and Control, 1983
The purpose of this paper is to discuss some properties of multivariable systems which have no analog in scalar systems.
J. Freudenberg, D. Looze
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On multivariate genetic systems

2009 IEEE International Conference on Fuzzy Systems, 2009
We take into account the problem of extending the Univariate Marginal Distribution Genetic Algorithm (UMDGA) modeling and analysis to the multivariate framework. In partic­ular, we introduce the basic general concepts and mathematical formalism to devise genetic algorithms useful to solve problems involving dependencies among genes.
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On the stability of multivariable feedback systems

2015 54th IEEE Conference on Decision and Control (CDC), 2015
In this paper, we consider the stability of a multivariable unity feedback system with an r × r rational proper transfer matrix G(s) in the forward path. The analysis is facilitated by introducing an “equivalent” scalar transfer function g(s) which consists of the sum of the determinants of all leading principal minors of G(s).
Lee H. Keel, Shankar P. Bhattacharyya
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Bidiagonal realization for multivariable systems

International Journal of Systems Science, 1992
Bidiagonal realization was first introduced by Policastro (1980) for SISO linear systems. A more general approach is presented here that allows definitions and computational procedures in its determination to apply also to the case of MIMO systems. A cyclic systems are also considered, i.e. systems requiring a block bidiagonal (derogatory) matrix to be
BLANCHINI, Franco, POLICASTRO M.
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On identification of multivariate Hammerstein systems

CCECE 2010, 2010
This paper presents a semi-parametric approach to the problem of identification of multivariate Hammerstein systems. A nonlinearity in general multivariate Hammerstein systems is represented by projecting the d-dimensional input signal onto one dimensional subset which, in turn, is mapped by a univariate nonparametric function to an internal signal of ...
Jiaqing Lv, Mirek Pawlak
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PARAMETRIZATIONS FOR MULTIVARIABLE ADAPTIVE SYSTEMS

IFAC Proceedings Volumes, 1983
Abstract This paper describes algorithms for model reference adaptive control of linear multivariable systems. A survey of recent work on MIMO direct adaptive control is presented, focusing on the general case of processes which are not decouplable by static state feedback.
J.M. Dion, L. Dugard
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