Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

Analytic models for the latency and steady-state throughput of TCP Tahoe, Reno, and SACK

Continuing the process of improvements made to TCP through the addition of new algorithms in Tahoe and Reno, TCP SACK aims to provide robustness to TCP in the presence of multiple losses from the same window. In this paper we present analytic models to estimate the latency and steady-state throughput of TCP Tahoe, Reno, and SACK and validate our models using both simulations and TCP traces collected from the Internet. In addition to being the first models for the latency of finite Tahoe and SACK flows, our model for the latency of TCP Reno gives a more accurate estimation of the transfer times than existing models. The improved accuracy is partly due to a more accurate modeling of the timeouts, evolution of cwnd during slow start and the delayed ACK timer. Our models also show that, under the losses introduced by the droptail queues which dominate most routers in the Internet, current implementations of SACK can fail to provide adequate protection against timeouts and a loss of roughly more than half the packets in a round will lead to timeouts. We also show that with independent losses SACK performs better than Tahoe and Reno and, as losses become correlated, Tahoe can outperform both Reno and SACK.     

Synthesis of ZSM‐5 Films and Monoliths with Bimodal Micro/Mesoscopic Structures

A route to synthesize ZSM‐5 crystals with a bimodal micro/mesoscopic pore system has been developed in this study; the successful incorporation of the mesopores within the ZSM‐5 structure was performed using tetrapropylammonium hydroxide (TPAOH)‐impregnated mesoporous materials containing carbon nanotubes in the pores, which were encapsulated in the ZSM‐5 crystals during a solid rearrangement process within the framework. Such mesoporous ZSM‐5 zeolites can be readily obtained as powders, thin films, or monoliths.     

Optimal pilot waveform assisted modulation for ultrawideband communications

Ultrawideband (UWB) transmissions induce pronounced frequency-selective fading effects in their multipath propagation. Multipath diversity gains can be collected to enhance performance, provided that the underlying channel can be estimated at the receiver. To this end, we develop a novel pilot waveform assisted modulation (PWAM) scheme that is tailored for UWB communications. We select our PWAM parameters by jointly optimizing channel estimation performance and information rate. The resulting transmitter design maximizes the average capacity, which is shown to be equivalent to minimizing the mean-square channel estimation error, and thereby achieves the Crame/spl acute/r-Rao lower bound. Application of PWAM to practical UWB systems is promising because it entails simple integrate-and-dump operations at the frame rate. Equally important, it offers a flexible UWB channel estimator, capable of striking desirable rate-performance tradeoffs depending on the channel coherence time.     

Effect of the Distribution of Manganese Ions on the Properties of Mn-Doped (Ba,Y)TiO3 PTCR Ceramics

The electrical properties and microstructure of (Ba,Y)TiO₃ PTCR ceramics were studied. The results indicate that the Mn ions increase the intergranular barrier height and produce a high-resistance layer on the grain surface. The temperature-dependent resistances of the grain bulk, surface layer, and grain boundaries, the temperature coefficient of resistance, and the magnitude of the varistor effect were assessed as a function of Mn content.     

QR factoring to compute the GCD of univariate approximate polynomials

We present a stable and practical algorithm that uses QR factors of the Sylvester matrix to compute the greatest common divisor (GCD) of univariate approximate polynomials over /spl Ropf/[x] or /spl Copf/[x]. An approximate polynomial is a polynomial with coefficients that are not known with certainty. The algorithm of this paper improves over previously published algorithms by handling the case when common roots are near to or outside the unit circle, by splitting and reversal if necessary. The algorithm has been tested on thousands of examples, including pairs of polynomials of up to degree 1000, and is now distributed as the program QRGCD in the SNAP package of Maple 9.     

Moving Least-Squares Differential Quadrature Method for Free Vibration of Antisymmetric Laminates

In this paper, the moving least-squares differential quadrature (MLSDQ) method is employed for free vibration of thick antisymmetric laminates based on the first-order shear deformation theory. The generalized displacements of the laminates are independently approximated with the centered moving least-squares (MLS) technique within each domain of influence. The MLS nodal shape functions and their partial derivatives are computed quickly through back-substitutions after only one LU decomposition. Subsequently, the weighting coefficients in the MLSDQ discretization are determined with the nodal partial derivatives of the MLS shape functions. The MLSDQ method combines the merits of both the differential quadrature and meshless methods which can be conveniently applied to complex domains and irregular discretizations without loss of implementation efficiency and numerical accuracy. The natural frequencies of the laminates with various edge conditions, ply angles, and shapes are calculated and compared with the existing solutions to study the numerical accuracy and stability of the MLSDQ method. Effects of support size, order of completeness of basis functions, and node irregularity on the numerical accuracy are investigated in detail.     

Derivation of a second-order switching surface in the boundary control of buck converters

A second-order switching surface in the boundary control of buck converters is derived in this letter. The formulated switching surface can make the overall converter exhibit better steady-state and transient behaviors than the one with a first-order switching surface. The switching surface is derived by estimating the state trajectory movement after a switching action, resulting in a high state trajectory velocity along the switching surface. This phenomenon accelerates the trajectory moving toward the target operating point. The proposed control scheme has been successfully applied to a 120-W buck converter. The large-signal performance and a comparison with the first-order switching surface have been studied.     

Science in High Magnetic Fields: What Could Be Learned?

High magnetic fields are one of the most powerful tools available to scientists for the study, modification and control of matter. This includes the knowledge on correlations effects, interaction mechanisms, structural information and understanding of mesoscopic effects. In this context, a review of recent scientific achievements at the Grenoble High Magnetic Laboratory is given to illustrate, on specific examples, the power of the Magnetic Field probe.     

Structural Changes Induced in Nonstoichiometric Titanium Carbide by High-Temperature Deformation

The microstructure evolution in nonstoichiometric titanium carbide is studied during high-temperature deformation at high strain rates and low strains (shock compression) and at slow strain rates and high strains (superplastic regime). The results demonstrate that high-temperature deformation in a broad range of strain rates offers a means of controlling the microstructure of titanium carbide. By varying deformation conditions, one can obtain materials differing in microstructure and chemical composition, in particular, with equilibrium and nonequilibrium microstructures. Accordingly, the physicochemical properties of such materials also differ.