Results 241 to 250 of about 32,211 (287)
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Dual Approximations in Optimal Control
SIAM Journal on Control and Optimization, 1984The following optimal control problem is considered: \[ (P)\quad \min imize\quad C(z)\quad subject\quad to\quad M(z)=0,\quad z\in {\mathcal Z}, \] where \({\mathcal Z}\) denotes the set of pairs \(z=(x,u)\) such that x: [0,1]\(\to {\mathbb{R}}^ n\) is absolutely continuous and u: [0,1]\(\to {\mathbb{R}}^ m\) is summable, and \(M(x,u)(t)=x'(t)-A(t)x(t ...
Hager, William W., Ianculescu, George D.
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Constrained approximate controllability
IEEE Transactions on Automatic Control, 2000Summary: Constrained approximate controllability for linear dynamical systems described by abstract differential equations with unbounded control operator is considered. Using methods of spectral analysis for linear self-adjoint operators and general constrained controllability results given by \textit{N. K. Son} [J. Math. Anal. Appl.
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Approximation in Control of Thermoelastic Systems
SIAM Journal on Control and Optimization, 1989Summary: This paper develops an abstract framework for analysis and approximation of linear thermoelastic control systems, and for design of finite- dimensional compensators. The thermoelastic systems in this paper consist of abstract wave and diffusion equations coupled in a skew self-adjoint fashion.
Gibson, J. S., Rosen, I. G., Tao, G.
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Approximate Classifiers with Controlled Accuracy
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications, 2019Performing exact computations can require significant resources. Approximate computing allows to alleviate resource constraints, sacrificing the accuracy of results. In this work, we consider a generalization of the classical packet classification problem. Our major contribution is to introduce various representations for approximate packet classifiers
Vitalii Demianiuk +2 more
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1994
In this chapter, we analyse three further matrix least squares estimation problems. The first is concerned with the task of approximating matrices by lower rank ones. This has immediate relevance to total least squares estimation and representations by linear neural networks. The section also serves as a prototype for linear system approximation.
Uwe Helmke, John B. Moore
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In this chapter, we analyse three further matrix least squares estimation problems. The first is concerned with the task of approximating matrices by lower rank ones. This has immediate relevance to total least squares estimation and representations by linear neural networks. The section also serves as a prototype for linear system approximation.
Uwe Helmke, John B. Moore
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Solvable approximations of control systems
The 23rd IEEE Conference on Decision and Control, 1984The paper is concerned with the construction of affine systems in the Crouch canonical form, defined on vector spaces, which approximate locally the input-output behaviour of a given smooth affine system. A similar problem of approximation by bilinear systems has been considered first by \textit{A. J. Krener} [SIAM J.
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Approximation of impulse controls
Computational Mathematics and Modeling, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Daryin, A. N., Minaeva, Yu. Yu.
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Approximate Identification for Robust Control
IFAC Proceedings Volumes, 1997Abstract This paper discusses results related to approximate identification for robust control. The criteria for modeling and identification are formulated in terms of ℒ or ℋ norm. Emphasis is made on the construction of a model set by specifying bases in function spaces ℒ, ℋ or in the disc algebra A.
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Constrained approximate boundary controllability
IEEE Transactions on Automatic Control, 1997The author gives necessary and sufficient conditions for constrained approximate boundary controllability for a class of linear systems described by partial differential equations of parabolic type with mixed boundary conditions. Some examples presented in detail illustrate the power of these criteria.
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Approximate Controllability for Degenerate Heat Equation with Bilinear Control
Journal of Systems Science and Complexity, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lingfei Li, Hang Gao 0001
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