Results 211 to 220 of about 2,629 (265)

Optimal control and approximations

, 2020
Zwart, Hans, Morris, Kirsten, Iftime, Orest   +2 more
openaire   +2 more sources

The frequency response of networks as open systems. [PDF]

Nat Commun
Nazerian A, Asllani M, Tyloo M, Ku WL, Sorrentino F.   +4 more
europepmc   +1 more source

Hybrid Robust Beamforming Optimization for LEO Satellite Communications Under DOA Estimation Errors in Spectrum Sharing Scenarios. [PDF]

Sensors (Basel)
Wang Y, Xie X, Jia J.
europepmc   +1 more source

Edge digital twin for coordinating flexible resources in distribution networks with communication constraints. [PDF]

Sci Rep
Guo J, Chen F, Liu D, Weng J, Ma S, Wang T.   +5 more
europepmc   +1 more source

Weaponizing cognitive bias in autonomous systems: a framework for black-box inference attacks. [PDF]

Front Artif Intell
Chu S, Chen Y.
europepmc   +1 more source

Computational link between motivational factors and cognitive deficits in depression

Stolicyn A, Romaniuk L, Lawrie SM, Seriès P.   +3 more
europepmc   +1 more source

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Approximate feedforward control

2015 10th Asian Control Conference (ASCC), 2015
Disturbances are inevitable in most control systems. They drive the systems away from their set points. It takes time for feedback control to reject them. The feedforward control offers great potentials for regulation performance if the disturbances are measurable.
Xian Li, Qing-Guo Wang, Wen-Jian Cai
openaire   +1 more source

Consistent Approximations and Approximate Functions and Gradients in Optimal Control

SIAM Journal on Control and Optimization, 2002
Summary: Because of the unavoidable use of numerical integration methods, such as Runge--Kutta or finite elements, the numerical solution of optimal control problems, with either ODE or PDE dynamics, is governed by a discretization parameter such as the integration mesh-size.
Olivier Pironneau, Elijah Polak
openaire   +2 more sources

Dual Approximations in Optimal Control

SIAM Journal on Control and Optimization, 1984
The 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.
openaire   +1 more source

Approximation in Control of Thermoelastic Systems

SIAM Journal on Control and Optimization, 1989
Summary: 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.
openaire   +1 more source