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The technique of splitting operators in perturbation control theory

Michail M. Konstantinov, Petko Hr. Petkov, Nikolaĭ D. Hristov (2005)

Kybernetika

The paper presents the technique of splitting operators, intended for perturbation analysis of control problems involving unitary matrices. Combined with the technique of Lyapunov majorants and the application of the Banach or Schauder fixed point principles, it allows to obtain rigorous non-local perturbation bounds for a set of sensitivity analysis problems. Among them are the reduction of linear systems into orthogonal canonical forms, the general feedback synthesis problem, and the pole assignment...

The tracking and regulation problem for a class of generalized systems

Antonio Tornambè (1998)

Kybernetika

The tracking and regulation problem is considered for a class of generalized systems, in case of exponential reference signals and of disturbance functions. First, the notions of steady-state response and of blocking zero, which are classical for linear time-invariant systems, are given for generalized systems. Then, the tracking and regulation problem is stated and solved for the class of generalized systems under consideration, giving a general design procedure. As a corollary of the effectiveness...

Time-variant Darlington synthesis and induced realizations

Derk Pik (2001)

International Journal of Applied Mathematics and Computer Science

For a block lower triangular contraction T, necessary and sufficient conditions are given in order that there exist block lower triangular contractions T_{1,1}, T_{2,1} and T_{2,2} such that T_{1,1} T U_T = [ ] T_{2,1} T_{2,2} is unitary. For the case when T^*_{1,1} and T_{2,2} have dense ranges, all such embeddings are described. Each unitary embedding of UT induces a contractive realization of T , and various properties of this realization are characterized in terms of the unitary embedding.

Towards robustness in neural network based fault diagnosis

Krzysztof Patan, Marcin Witczak, Józef Korbicz (2008)

International Journal of Applied Mathematics and Computer Science

Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as neural networks become more and more popular in industrial applications of fault diagnosis. Taking into account the two crucial aspects, i.e., the nonlinear behaviour of the system being diagnosed as well as the robustness of a fault diagnosis scheme with...

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