The optimal and reliable performance of doubly fed induction generator is essential for the efficient and optimal operation of wind energy conversion systems. This paper considers the nonlinear dynamic of a DFIG linked to a power grid and presents a new robust model predictive control technique of active and reactive power by the use of the linear matrix inequality in DFIG-based WECS. The control law is obtained through the LMI-based model predictive control that allows considering both economic and tracking factors by optimization of an objective function, constraints on control signal and states of system and effects of nonlinearities, generator parameter uncertainties and external disturbances. Robust stability in the face of bounded disturbances and generator uncertainty is shown using Lyapunov technique. Numerical simulations show that the proposed control method is able to meet the desired specification in active and reactive power control in the presence of varieties of wind speed and pitch angle.
Endothelin B (ETB) receptors present in abundance the central nervous system (CNS) have been shown to have significant implications in its development and neurogenesis. We have targeted ETB receptors stimulation using a highly specific agonist, IRL-1620, to treat CNS disorders. In a rat model of cerebral ischemia intravenous administration IRL-1620 significantly reduced infarct volume and improved neurological and motor functions compared to control. This improvement, in part, is due to an increase in neuroregeneration. We also investigated the role of IRL-1620 in animal models of Alzheimer’s disease (AD). IRL-1620 improved learning and memory, reduced oxidative stress and increased VEGF and NGF in Aβ treated rats. IRL-1620 also improved learning and memory in an aged APP/PS1 transgenic mouse model of AD. These promising findings prompted us to initiate human studies. Successful chemistry, manufacturing and control along with mice, rat and dog toxicological studies led to completion of a human Phase I study in healthy volunteers. We found that a dose of 0.6 μg/kg of IRL-1620 can be safely administered, three times every four hours, without any adverse effect. A Phase II clinical study with IRL-1620 has been initiated in patients with cerebral ischemia and mild to moderate AD., A. Gulati, M. G. Hornick, S. Briyal, M. S. Lavhale., and Seznam literatury
In this short note, we introduce a new architecture for spiking perceptron: The actual output is a linear combination of the firing time of the perceptron and the spiking intensity (the gradient of the state function) at the firing time. It is shown by numerical experiments that this novel spiking perceptron can solve the XOR problem, while a classical spiking neuron usually needs a hidden layer to solve the XOR problem.
In current textbooks the use of Chebyshev nodes with Newton interpolation is advocated as the most efficient numerical interpolation method in terms of approximation accuracy and computational effort. However, we show numerically that the approximation quality obtained by Newton interpolation with Fast Leja (FL) points is competitive to the use of Chebyshev nodes, even for extremely high degree interpolation. This is an experimental account of the analytic result that the limit distribution of FL points and Chebyshev nodes is the same when letting the number of points go to infinity. Since the FL construction is easy to perform and allows to add interpolation nodes on the fly in contrast to the use of Chebyshev nodes, our study suggests that Newton interpolation with FL points is currently the most efficient numerical technique for polynomial interpolation. Moreover, we give numerical evidence that any reasonable function can be approximated up to machine accuracy by Newton interpolation with FL points if desired, which shows the potential of this method.
Many recent observations have shown that resonances have a wide variety of effects in planetary rings: spiral waves, gaps, confinement, sharp edges, arcs. While resonances are known to be associated with such structures, the role of inter-particle collisions is still poorly understood, although necessary to explain the long term evolution of the rings.
In an effort to better understand the associated dynamics, we have performed numerical simulations of colliding particles orbiting a massive central planet. The code simulates the 3-D motion of 100 identical spherical particles orbiting a massive cental body and suffering inelastic collisions while being perturbed by one or more satellites.
We used this code to explore in more details the dynamics of are rings, and to explain in particular the reeent observations of are structures around Neptune. Clusters of particles at a satellite’s Lagrangian point {L4 or L5) are shown to be dispersed by dissipative effects. However, a second satellite can stabilize the system by providing sufficient energy through a Lindblaďs
resonance m±l:m. Other dynamically equivalent configurations (e.g. only one satellite, but with an eccentric orbit) can also stabilize are sytems, in accord with current analytical models.
We examine the roles of collisions at Lindblad and corotation resonances in various cases. Arcs remain at the potential maxima created by the corotations. However, stability requires that the satellites’ masses be within a limited range: small satellites cannot provide enough energy while large ones give too much, so the arc can disperse.
A new functional ANOVA test, with a graphical interpretation of the result, is presented. The test is an extension of the global envelope test introduced by Myllymäki et al. (2017, Global envelope tests for spatial processes, J. R. Statist. Soc. B 79, 381-404, doi: 10.1111/rssb.12172). The graphical interpretation is realized by a global envelope which is drawn jointly for all samples of functions. If a mean function computed from the empirical data is out of the given envelope, the null hypothesis is rejected with the predetermined significance level α. The advantages of the proposed one-way functional ANOVA are that it identifies the domains of the functions which are responsible for the potential rejection. We introduce two versions of this test: the first gives a graphical interpretation of the test results in the original space of the functions and the second immediately offers a post-hoc test by identifying the significant pair-wise differences between groups. The proposed tests rely on discretization of the functions, therefore the tests are also applicable in the multidimensional ANOVA problem. In the empirical part of the article, we demonstrate the use of the method by analyzing fiscal decentralization in European countries.
In this paper, we propose a novel hybrid metaheuristic algorithm, which integrates a Threshold Accepting algorithm (TA) with a traditional Particle Swarm Optimization (PSO) algorithm. We used the TA as a catalyst in speeding up convergence of PSO towards the optimal solution. In this hybrid, at the end of every iteration of PSO, the TA is invoked probabilistically to refine the worst particle that lags in the race of finding the solution for that iteration. Consequently the worst particle will be refined in the next iteration. The robustness of the proposed approach has been tested on 34 unconstrained optimization problems taken from the literature. The proposed hybrid demonstrates superior preference in terms of functional evaluations and success rate for 30 simulations conducted.
We mainly prove: Assume that each output function of DCNN is bounded on R and satisfies the Lipschitz condition, if is a periodic function with period ω each i, then DCNN has a unique ω-period solution and all other solutions of DCNN converge exponentially to it, where is a Lipschitz constant of for i=1,2,...,n.
We report on detailed studies of the absorption line spectrum and spectroscopic orbit of the binary BN2.5Ib star HD 235679. We also give ao preliminary report on our study of the Hα emission line profiles from this perplexing system. Hipparcos and Tycho2 astrometric data allow us to place limits on the distance to the system. The lack of a measurable reflection effect in the Hipparcos photometry allows us to rule out the possibility that the massive invisible star is cool and fills its Roche lobe. Thus, by process of elimination, the invisible star must be hot or a black hole. The properties of the Hα profiles suggest that the invisible star is somewhat hotter, and has a stronger wind than HD235679.
The present paper studies the \textit{approximate value iteration} (AVI) algorithm for the average cost criterion with bounded costs and Borel spaces. It is shown the convergence of the algorithm and provided a performance bound assuming that the model satisfies a standard continuity-compactness assumption and a uniform ergodicity condition. This is done for the class of approximation procedures that can be represented by linear positive operators which give exact representation of constant functions and also satisfy certain continuity property. The main point is that these operators define transition probabilities on the state space of the controlled system. This has the following important consequences: (a) the approximating function is the average value of the target function with respect to the induced transition probability; (b) the approximation step in the AVI algorithm can be seen as a perturbation of the original Markov model; (c) the perturbed model inherits the ergodicity properties imposed on the original Markov model. These facts allow to bound the AVI algorithm performance in terms of the accuracy of the approximations given by this kind of operators for the primitive data model, namely, the one-step reward function and the system transition law. The bounds are given in terms of the supremum norm of bounded functions and the total variation norm of finite-signed measures. The results are illustrated with numerical approximations for a class of single item inventory systems with linear order cost, no set-up cost and no back-orders.