Two-Stage Extended Kalman Filters with Derivative-Free Local Linearizations

This paper proposes a derivative-free two-stage extended Kalman filter (2-EKF) especially suited for state and parameter identification of mechanical oscillators under Gaussian white noise. Two sources of modeling uncertainties are considered: (1) errors in linearization, and (2) an inadequate system model. The state vector is presently composed of the original dynamical/parameter states plus the so-called bias states accounting for the unmodeled dynamics. An extended Kalman estimation concept is applied within a framework predicated on explicit and derivative-free local linearizations (DLL) of nonlinear drift terms in the governing stochastic differential equations (SDEs). The original and bias states are estimated by two separate filters; the bias filter improves the estimates of the original states. Measurements are artificially generated by corrupting the numerical solutions of the SDEs with noise through an implicit form of a higher-order linearization. Numerical illustrations are provided for a few single- and multidegree-of-freedom nonlinear oscillators, demonstrating the remarkable promise that 2-EKF holds over its more conventional EKF-based counterparts. DOI: 10.1061/(ASCE)EM.1943-7889.0000255. (C) 2011 American Society of Civil Engineers.

Magnetic order of the hexagonal rare-earth manganite Dy(0.5)Y(0.5)MnO(3)

Hexagonal Dy(0.5)Y(0.5)MnO(3), a multiferroic rare-earth manganite with geometrically frustrated antiferromagnetism, has been investigated with single-crystal neutron diffraction measurements. Below 3.4 K magnetic order is observed on both the Mn (antiferromagnetic) and Dy (ferrimagnetic) sublattices that is identical to that of undiluted hexagonal DyMnO(3) at low temperature. The Mn moments undergo a spin reorientation transition between 3.4 K and 10 K, with antiferromagnetic order of the Mn sublattice persisting up to 70 K; the antiferromagnetic order in this phase is distinct from that observed in undiluted (h) DyMnO(3), yielding a qualitatively new phase diagram not seen in other hexagonal rare-earth manganites. A magnetic field applied parallel to the crystallographic c axis will drive a transition from the antiferromagnetic phase into the low-temperature ferrimagnetic phase with little hysteresis.

A Nonlinear Voltage Regulator With One Tunable Parameter for Multimachine Power Systems

This paper proposes a nonlinear voltage regulator with one tunable parameter for multimachine power systems. Based on output feedback linearization, this regulator can achieve simultaneous voltage regulation and small-signal performance objectives. Conventionally output feedback linearization has been used for voltage regulator design by taking infinite bus voltage as reference. Unfortunately, this controller has poor small-signal performance and cannot be applied to multimachine systems without the estimation of the equivalent external reactance seen from the generator. This paper proposes a voltage regulator design by redefining the rotor angle at each generator with respect to the secondary voltage of the step-up transformer as reference instead of a common synchronously rotating reference frame. Using synchronizing and damping torques analysis, we show that the proposed voltage regulator achieves simultaneous voltage regulation and damping performance over a range of system and operating conditions by controlling the relative angle between the generator internal voltage angle delta and the secondary voltage of the step up transformer. The performance of the proposed voltage regulator is evaluated on a single machine infinite bus system and two widely used multimachine test systems.

Lamb wave based identification and parameter estimation of corrosion in metallic plate structure using a circular PWAS array

A circular array of Piezoelectric Wafer Active Sensor (PWAS) has been employed to detect surface damages like corrosion using lamb waves. The array consists of a number of small PWASs of 10 mm diameter and 1 mm thickness. The advantage of a circular array is its compact arrangement and large area of coverage for monitoring with small area of physical access. Growth of corrosion is monitored in a laboratory-scale set-up using the PWAS array and the nature of reflected and transmitted Lamb wave patterns due to corrosion is investigated. The wavelet time-frequency maps of the sensor signals are employed and a damage index is plotted against the damage parameters and varying frequency of the actuation signal (a windowed sine signal). The variation of wavelet coefficient for different growth of corrosion is studied. Wavelet coefficient as function of time gives an insight into the effect of corrosion in time-frequency scale. We present here a method to eliminate the time scale effect which helps in identifying easily the signature of damage in the measured signals. The proposed method becomes useful in determining the approximate location of the corrosion with respect to the location of three neighboring sensors in the circular array. A cumulative damage index is computed for varying damage sizes and the results appear promising.

Accurate Parameter Estimation of Contaminant Transport Inverse Problem using Paartaicle Swarm Optimization

Swarm Intelligence techniques such as particle swarm optimization (PSO) are shown to be incompetent for an accurate estimation of global solutions in several engineering applications. This problem is more severe in case of inverse optimization problems where fitness calculations are computationally expensive. In this work, a novel strategy is introduced to alleviate this problem. The proposed inverse model based on modified particle swarm optimization algorithm is applied for a contaminant transport inverse model. The inverse models based on standard-PSO and proposed-PSO are validated to estimate the accuracy of the models. The proposed model is shown to be out performing the standard one in terms of accuracy in parameter estimation. The preliminary results obtained using the proposed model is presented in this work.

Wave dispersion in a cellular composite with modulated microstructure

In this paper we report a modeling technique and analysis of wave dispersion in a cellular composite laminate with spatially modulated microstructure, which can be modeled by parameterization and homogenization in an appropriate length scale. Higher order beam theory is applied and the system of wave equations are derived. Homogenization of these equations are carried out in the scale of wavelength and frequency of the individual wave modes. Smaller scale scattering below the order of cell size are filtered out in the present approach. The longitudinal dispersion relations for different values of a modulation parameter are analyzed which indicates the existence of stop and pass band patterns. Dispersion relations for flexural-shear case are also analyzed which indicates a tendency toward forming the stop and pass bands for increasing values of a shear stiffness modulation parameter. The effect the phase angle (θ) of the incident wave indicates the existence more number of alternative stop bands and pass bands for θ = 45°.

A Neuro-Adaptive Approach for Robust Control of High Performance Aircrafts with Parameter Inaccuracies

For high performance aircrafts, the flight control system needs to be quite effective in both assuring accurate tracking of pilot commands, while simultaneously assuring overall stability of the aircraft. In addition, the control system must also be sufficiently robust to cater to possible parameter variations. The primary aim of this paper is to enhance the robustness of the controller for a HPA using neuro-adaptive control design. Here the architecture employs a network of Gaussian Radial basis functions to adaptively compensate for the ignored system dynamics. A stable weight mechanism is determined using Lyapunov theory. The network construction and performance of the resulting controller are illustrated through simulations with a low-fidelity six –DOF model of F16 that is available in open literature.

Quantum destruction of spiral order in two-dimensional frustrated magnets

We study the fate of spin-1/2 spiral-ordered two-dimensional quantum antiferromagnets that are disordered by quantum fluctuations. A crucial role is played by the topological point defects of the spiral phase, which are known to have a Z(2) character. Previous works established that a nontrivial quantum spin-liquid phase results when the spiral is disordered without proliferating the Z(2) vortices. Here, we show that when the spiral is disordered by proliferating and condensing these vortices, valence-bond solid ordering occurs due to quantum Berry phase effects. We develop a general theory for this latter phase transition and apply it to a lattice model. This transition potentially provides a new example of a Landau-forbidden deconfined quantum critical point.

TeV scale implications of non commutative space time in laboratory frame with polarized beams

We analyze e(+)e(-) -> gamma gamma, e(-)gamma -> e(-)gamma and gamma gamma -> e(+)e(-) processes within the Seiberg-Witten expanded noncommutative scenario using polarized beams. With unpolarized beams the leading order effects of non commutativity starts from second order in non commutative(NC) parameter i.e. O(Theta(2)), while with polarized beams these corrections appear at first order (O(Theta')) in cross section. The corrections in Compton case can probe the magnetic component(Theta(B)) while in Pair production and Pair annihilation probe the electric component((Theta) over right arrow (E)) of NC parameter. We include the effects of earth rotation in our analysis. This study is done by investigating the effects of non commutativity on different time averaged cross section observables. The results which also depends on the position of the collider, can provide clear and distinct signatures of the model testable at the International Linear Collider(ILC).

Model-following Neuro-adaptive approach for robust control of high performance aircrafts

Based on dynamic inversion, a relatively straightforward approach is presented in this paper for nonlinear flight control design of high performance aircrafts, which does not require the normal and lateral acceleration commands to be first transferred to body rates before computing the required control inputs. This leads to substantial improvement of the tracking response. Promising results are obtained from six degree-offreedom simulation studies of F-16 aircraft, which are found to be superior as compared to an existing approach (which is also based on dynamic inversion). The new approach has two potential benefits, namely reduced oscillatory response (including elimination of non-minimum phase behavior) and reduced control magnitude. Next, a model-following neuron-adaptive design is augmented the nominal design in order to assure robust performance in the presence of parameter inaccuracies in the model. Note that in the approach the model update takes place adaptively online and hence it is philosophically similar to indirect adaptive control. However, unlike a typical indirect adaptive control approach, there is no need to update the individual parameters explicitly. Instead the inaccuracy in the system output dynamics is captured directly and then used in modifying the control. This leads to faster adaptation, which helps in stabilizing the unstable plant quicker. The robustness study from a large number of simulations shows that the adaptive design has good amount of robustness with respect to the expected parameter inaccuracies in the model.

Phase Characterization and Study of Molecular Order of a Three-Ring Mesogen by (13)C NMR in Smectic C and Nematic Phases

Molecules exhibiting a thermotropic liquid-crystalline property have acquired significant importance due to their sensitivity to external stimuli such as temperature, mechanical forces, and electric and magnetic fields. As a result, several novel mesogens have been synthesized by the introduction of various functional groups in the vicinity of the aromatic core as well as in the side chains and their properties have been studied. In the present study, we report three-ring mesogens with hydroxyl groups at one terminal. These mesogens were synthesized by a multistep route, and structural characterization was accomplished by spectral techniques. The mesophase properties were studied by hot-stage optical polarizing microscopy, differential scanning calorimetry, and small-angle X-ray scattering. An enantiotropic nematic phase was noticed for lower homologues, while an additional smectic C phase was found for higher homologues. Solid-state high-resolution natural abundance (13)C NMR studies of a typical mesogen in the solid phase and in the mesophases have been carried out. The (13)C NMR spectrum of the mesogen in the smectic C and nematic phases indicated spontaneous alignment of the molecule in the magnetic field. By utilizing the two-dimensional separated local field (SLF) NMR experiment known as SAMPI4, (13)C-(1)H dipolar couplings have been obtained, which were utilized to determine the orientational order parameters of the mesogen.

Stochastic Algorithms for Discrete Parameter Simulation Optimization

We present two efficient discrete parameter simulation optimization (DPSO) algorithms for the long-run average cost objective. One of these algorithms uses the smoothed functional approximation (SFA) procedure, while the other is based on simultaneous perturbation stochastic approximation (SPSA). The use of SFA for DPSO had not been proposed previously in the literature. Further, both algorithms adopt an interesting technique of random projections that we present here for the first time. We give a proof of convergence of our algorithms. Next, we present detailed numerical experiments on a problem of admission control with dependent service times. We consider two different settings involving parameter sets that have moderate and large sizes, respectively. On the first setting, we also show performance comparisons with the well-studied optimal computing budget allocation (OCBA) algorithm and also the equal allocation algorithm. Note to Practitioners-Even though SPSA and SFA have been devised in the literature for continuous optimization problems, our results indicate that they can be powerful techniques even when they are adapted to discrete optimization settings. OCBA is widely recognized as one of the most powerful methods for discrete optimization when the parameter sets are of small or moderate size. On a setting involving a parameter set of size 100, we observe that when the computing budget is small, both SPSA and OCBA show similar performance and are better in comparison to SFA, however, as the computing budget is increased, SPSA and SFA show better performance than OCBA. Both our algorithms also show good performance when the parameter set has a size of 10(8). SFA is seen to show the best overall performance. Unlike most other DPSO algorithms in the literature, an advantage with our algorithms is that they are easily implementable regardless of the size of the parameter sets and show good performance in both scenarios.

AC Breakdown Characteristics of Epoxy Nanocomposites

Experiments were conducted to measure the ac breakdown strength of epoxy alumina nanocomposites with different filler loadings of 0.1, 1 and 5 wt%. The experiments were performed as per the ASTM D 149 standard on samples of thickness 0.5 mm, 1 mm and 3 mm in order to study the effect of thickness on the ac breakdown strength of epoxy nanocomposites. In the case of epoxy alumina nanocomposites it was observed that the ac breakdown strength was marginally lower for 0.1 wt% and 1 wt% filler loadings and then increased at 5 wt% filler loading as compared to the unfilled epoxy. The Weibull shape parameter (beta) increased with the addition of nanoparticles to epoxy as well as with the increasing sample thickness for all the filler loadings considered. DSC analysis was done to study the material properties at the filler resin interface in order to understand the effect of the filler loading and thereby the influence of the interface on the ac breakdown strength of epoxy nanocomposites. It was also observed that the decrease in ac electric breakdown strength with an increase in sample thickness follows an inverse power-law dependence. In addition, the ac breakdown strength of epoxy silica nanocomposites have also been studied in order to understand the influence of the filler type on the breakdown strength.

An interior penalty method for a sixth-order elliptic equation

We derive and study a C(0) interior penalty method for a sixth-order elliptic equation on polygonal domains. The method uses the cubic Lagrange finite-element space, which is simple to implement and is readily available in commercial software. After introducing some notation and preliminary results, we provide a detailed derivation of the method. We then prove the well-posedness of the method as well as derive quasi-optimal error estimates in the energy norm. The proof is based on replacing Galerkin orthogonality with a posteriori analysis techniques. Using this approach, we are able to obtain a Cea-like lemma with minimal regularity assumptions on the solution. Numerical experiments are presented that support the theoretical findings.