17,490 research outputs found
A scalable line-independent design algorithm for voltage and frequency control in AC islanded microgrids
We propose a decentralized control synthesis procedure for stabilizing
voltage and frequency in AC Islanded microGrids (ImGs) composed of Distributed
Generation Units (DGUs) and loads interconnected through power lines. The
presented approach enables Plug-and-Play (PnP) operations, meaning that DGUs
can be added or removed without compromising the overall ImG stability. The
main feature of our approach is that the proposed design algorithm is
line-independent. This implies that (i) the synthesis of each local controller
requires only the parameters of the corresponding DGU and not the model of
power lines connecting neighboring DGUs, and (ii) whenever a new DGU is plugged
in, DGUs physically coupled with it do not have to retune their regulators
because of the new power line connected to them. Moreover, we formally prove
that stabilizing local controllers can be always computed, independently of the
electrical parameters. Theoretical results are validated by simulating in PSCAD
the behavior of a 10-DGUs ImG
Multifractal analysis of discretized X-ray CT images for the characterization of soil macropore structures
A correct statistical model of soil pore structure can be critical for understanding flow and transport processes in soils, and creating synthetic soil pore spaces for hypothetical and model testing, and evaluating similarity of pore spaces of different soils. Advanced visualization techniques such as X-ray computed tomography (CT) offer new opportunities of exploring heterogeneity of soil properties at horizon or aggregate scales. Simple fractal models such as fractional Brownian motion that have been proposed to capture the complex behavior of soil spatial variation at field scale rarely simulate irregularity patterns displayed by spatial series of soil properties. The objective of this work was to use CT data to test the hypothesis that soil pore structure at the horizon scale may be represented by multifractal models. X-ray CT scans of twelve, water-saturated, 20-cm long soil columns with diameters of 7.5 cm were analyzed. A reconstruction algorithm was applied to convert the X-ray CT data into a stack of 1480 grayscale digital images with a voxel resolution of 110 microns and a cross-sectional size of 690 × 690 pixels. The images were binarized and the spatial series of the percentage of void space vs. depth was analyzed to evaluate the applicability of the multifractal model. The series of depth-dependent macroporosity values exhibited a well-defined multifractal structure that was revealed by singularity and Rényi spectra. The long-range dependencies in these series were parameterized by the Hurst exponent. Values of the Hurst exponent close to one were observed indicating the strong persistence in variations of porosity with depth. The multifractal modeling of soil macropore structure can be an efficient method for parameterizing and simulating the vertical spatial heterogeneity of soil pore space
An application of eigenspace methods to symmetric flutter suppression
An eigenspace assignment approach to the design of parameter insensitive control laws for linear multivariable systems is presented. The control design scheme utilizes flexibility in eigenvector assignments to reduce control system sensitivity to changes in system parameters. The methods involve use of the singular value decomposition to provide an exact description of allowable eigenvectors in terms of a minimum number of design parameters. In a design example, the methods are applied to the problem of symmetric flutter suppression in an aeroelastic vehicle. In this example the flutter mode is sensitive to changes in dynamic pressure and eigenspace methods are used to enhance the performance of a stabilizing minimum energy/linear quadratic regulator controller and associated observer. Results indicate that the methods provide feedback control laws that make stability of the nominal closed loop systems insensitive to changes in dynamic pressure
Finding sparse solutions of systems of polynomial equations via group-sparsity optimization
The paper deals with the problem of finding sparse solutions to systems of
polynomial equations possibly perturbed by noise. In particular, we show how
these solutions can be recovered from group-sparse solutions of a derived
system of linear equations. Then, two approaches are considered to find these
group-sparse solutions. The first one is based on a convex relaxation resulting
in a second-order cone programming formulation which can benefit from efficient
reweighting techniques for sparsity enhancement. For this approach, sufficient
conditions for the exact recovery of the sparsest solution to the polynomial
system are derived in the noiseless setting, while stable recovery results are
obtained for the noisy case. Though lacking a similar analysis, the second
approach provides a more computationally efficient algorithm based on a greedy
strategy adding the groups one-by-one. With respect to previous work, the
proposed methods recover the sparsest solution in a very short computing time
while remaining at least as accurate in terms of the probability of success.
This probability is empirically analyzed to emphasize the relationship between
the ability of the methods to solve the polynomial system and the sparsity of
the solution.Comment: Journal of Global Optimization (2014) to appea
Cross-coupled doa trackers
A new robust, low complexity algorithm for multiuser tracking is proposed, modifying the two-stage parallel architecture of the estimate-maximize (EM) algorithm. The algorithm copes with spatially colored noise, large differences in source powers, multipath, and crossing trajectories. Following a discussion on stability, the simulations demonstrate an asymptotic and tracking behavior that neither the EM nor a nonparallelized tracker can emulate.Peer ReviewedPostprint (published version
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