82 research outputs found
Self-organizing input space for control of structures
We propose a novel type of neural networks for structural control, which comprises an adaptive input space. This feature is purposefully designed for sequential input selection during adaptive identification and control of nonlinear systems, which allows the input space to be organized dynamically, while the excitation is occurring. The neural network has the main advantages of (1) automating the input selection process for time series that are not known a priori; (2) adapting the representation to nonstationarities; and (3) using limited observations. The algorithm designed for the adaptive input space assumes local quasi-stationarity of the time series, and embeds local maps sequentially in a delay vector using the embedding theorem. The input space of the representation, which in our case is a wavelet neural network, is subsequently updated. We demonstrate that the neural net has the potential to significantly improve convergence of a black-box model in adaptive tracking of a nonlinear system. Its performance is further assessed in a full-scale simulation of an existing civil structure subjected to nonstationary excitations (wind and earthquakes), and shows the superiority of the proposed method
Oblique triangular antiferromagnetic phase in CsCuCoCl
The spin-1/2 stacked triangular antiferromagnet CsCuCoCl with
undergoes two phase transitions at zero field. The
low-temperature phase is produced by the small amount of Co doping. In
order to investigate the magnetic structures of the two ordered phases, the
neutron elastic scattering experiments have been carried out for the sample
with . It is found that the intermediate phase is identical to
the ordered phase of CsCuCl, and that the low-temperature phase is an
oblique triangular antiferromagnetic phase in which the spins form a triangular
structure in a plane tilted from the basal plane. The tilting angle which is
42 at K decreases with increasing temperature, and becomes
zero at K. An off-diagonal exchange term is proposed as the
origin of the oblique phase.Comment: 6 pages, 7 figure
The application of parameter sensitivity analysis methods to inverse simulation models
Knowledge of the sensitivity of inverse solutions to variation of parameters of a model can be very useful in making engineering design decisions. This paper describes how parameter sensitivity analysis can be carried out for
inverse simulations generated through approximate transfer function inversion methods and also by the use of feedback principles. Emphasis is placed on the use of sensitivity models and the paper includes examples and a case study involving a model of an underwater vehicle. It is shown that the use of sensitivity models can provide physical understanding of inverse simulation solutions that is not directly available using parameter sensitivity analysis methods that involve parameter perturbations and response
differencing
Universal quantum interfaces
To observe or control a quantum system, one must interact with it via an
interface. This letter exhibits simple universal quantum interfaces--quantum
input/output ports consisting of a single two-state system or quantum bit that
interacts with the system to be observed or controlled. It is shown that under
very general conditions the ability to observe and control the quantum bit on
its own implies the ability to observe and control the system itself. The
interface can also be used as a quantum communication channel, and multiple
quantum systems can be connected by interfaces to become an efficient universal
quantum computer. Experimental realizations are proposed, and implications for
controllability, observability, and quantum information processing are
explored.Comment: 4 pages, 3 figures, RevTe
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