Temat: L2 norm - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Optimal factors in Vladimir Markovs inequality in L2 norm
Autorzy:: Baran, M.
Kowalska, A.
Ozorka, P.
Powiązania:: https://bibliotekanauki.pl/articles/93076.pdf
Data publikacji:: 2018
Wydawca:: Państwowa Wyższa Szkoła Zawodowa w Tarnowie
Tematy:: Markov inequality
L2 norm
nierówność Markowa
norma L2
Opis:: In this paper we discuss a problem of computation of constants in Vladimir Markov's type inequality in L2 norm on the interval [-1, 1].
Źródło:: Science, Technology and Innovation; 2018, 2, 1; 64-73
2544-9125
Pojawia się w:: Science, Technology and Innovation
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Numerical error bound of optimal control for homogeneous linear systems
Autorzy:: Daraghmeh, Adnan
Qatanani, Naji
Powiązania:: https://bibliotekanauki.pl/articles/229410.pdf
Data publikacji:: 2019
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: time-invariant systems
quadratic cost function
linear quadratic regulator
algebraic Riccati equation
Hamiltonian function
L2 norm
Opis:: In this article we focus on the balanced truncation linear quadratic regulator (LQR) with constrained states and inputs. For closed-loop, we want to use the LQR to find an optimal control that minimizes the objective function which called "the quadratic cost function” with respect to the constraints on the states and the control input. In order to do that we have used formal asymptotes for the Pontryagin maximum principle (PMP) and we introduce an approach using the so called The Hamiltonian Function and the underlying algebraic Riccati equation. The theoretical results are validated numerically to show that the model order reduction based on open-loop balancing can also give good closed-loop performance.
Źródło:: Archives of Control Sciences; 2019, 29, 2; 323-337
1230-2384
Pojawia się w:: Archives of Control Sciences
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 3.

Tytuł:: Iterative-interpolation algorithms for L2 model reduction
Autorzy:: Krajewski, W.
Viaro, U.
Powiązania:: https://bibliotekanauki.pl/articles/970959.pdf
Data publikacji:: 2009
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: linear systems
model reduction
output-error minimization
L2 norm
Krylov subspaces
Arnoldi's algorithm
Opis:: This paper is concerned with the construction of reduced-order models for high-order linear systems in such a way that the L2 norm of the impulse-response error is minimized. Two convergent algorithms that draw on previous procedures presented by the same authors, are suggested: one refers to s-domain representations, the other to time-domain state-space representations. The algorithms are based on an iterative scheme that, at any step, satisfies certain interpolation constraints deriving from the optimality conditions. To make the algorithms suitable to the reduction of very large-scale systems, resort is made to Krylov subspaces and Arnoldi's method. The performance of the reduction algorithms is tested on two benchmark examples.
Źródło:: Control and Cybernetics; 2009, 38, 2; 543-554
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

Artykuł

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