Generalized model predictive static programming and its application to 3D impact angle constrained guidance of air-to-surface missiles

A new `generalized model predictive static programming (G-MPSP)' technique is presented in this paper in the continuous time framework for rapidly solving a class of finite-horizon nonlinear optimal control problems with hard terminal constraints. A key feature of the technique is backward propagation of a small-dimensional weight matrix dynamics, using which the control history gets updated. This feature, as well as the fact that it leads to a static optimization problem, are the reasons for its high computational efficiency. It has been shown that under Euler integration, it is equivalent to the existing model predictive static programming technique, which operates on a discrete-time approximation of the problem. Performance of the proposed technique is demonstrated by solving a challenging three-dimensional impact angle constrained missile guidance problem. The problem demands that the missile must meet constraints on both azimuth and elevation angles in addition to achieving near zero miss distance, while minimizing the lateral acceleration demand throughout its flight path. Both stationary and maneuvering ground targets are considered in the simulation studies. Effectiveness of the proposed guidance has been verified by considering first order autopilot lag as well as various target maneuvers.

Linear and nonlinear optical studies on 3,6-bis (2 pyridyl) pyridazine

3,6-Bis (2 pyridyl) pyridazine has been synthesized and characterized by NMR, XRD and elemental analyses. The vibrational studies were carried out by using FTIR and Raman spectroscopy and the modes of vibrations were analysed and compared with the theoretically calculated values. The nonlinear optical property of the title compound was examined by Kurtz-Perry method and Hyper Raleigh scattering with the fundamental wavelength of 1064nm. This compound possesses less SHG efficiency but large first hyperpolarizability. (C) 2013 Elsevier GmbH. All rights reserved.

A scaled unscented transformation based directed Gaussian sum filter for nonlinear dynamic system identification

Impoverishment of particles, i.e. the discretely simulated sample paths of the process dynamics, poses a major obstacle in employing the particle filters for large dimensional nonlinear system identification. A known route of alleviating this impoverishment, i.e. of using an exponentially increasing ensemble size vis-a-vis the system dimension, remains computationally infeasible in most cases of practical importance. In this work, we explore the possibility of unscented transformation on Gaussian random variables, as incorporated within a scaled Gaussian sum stochastic filter, as a means of applying the nonlinear stochastic filtering theory to higher dimensional structural system identification problems. As an additional strategy to reconcile the evolving process dynamics with the observation history, the proposed filtering scheme also modifies the process model via the incorporation of gain-weighted innovation terms. The reported numerical work on the identification of structural dynamic models of dimension up to 100 is indicative of the potential of the proposed filter in realizing the stated aim of successfully treating relatively larger dimensional filtering problems. (C) 2013 Elsevier Ltd. All rights reserved.

Electric field activated nonlinear anisotropic charge transport in doped polypyrrole

Electric field activated nonlinear transport is investigated in polypyrrole thin film in both in-plane and out-of-plane geometries down to 5 K and strong anisotropy is observed. A morphological model is suggested to explain the anisotropy through inter-chain and intra-chain transport. The deviation from the variable range hopping at low temperature is accounted by fluctuation assisted transport. From Zabrodaskii plots, it is found that electric field can tune the transport from insulating to metallic regime. Glazman-Matveev model is used to describe the nonlinear conduction. Field scaling analysis shows that conductance data at different temperature falls on to a single curve. Nonlinearity exponent, m(T) and characteristic length, L-E are estimated to characterize the transport in both the geometries. (C) 2013 AIP Publishing LLC.

Chemical vapor detection using nonlinear electrical properties of carbon nanotube bundles

We demonstrate the electrical transport behavior of carbon nanotubes (CNTs) upon exposure to organic analytes (namely ethanol, benzene, acetone and toluene). The resulting nonlinear current-voltage characteristics revealed a power law dependence of the differential conductivity on the applied bias voltage. Moreover, suppression of differential conductivity at zero bias is found to be dependent on different selective analytes. The power law exponent values have been monitored before, during and after exposure to the chemicals, which revealed a reversible change in the number of electron conducting channels. Therefore, the reduction in the number of conductive paths can be attributed to the interaction of the chemical analyte on the CNT surfaces, which causes a decrease in the differential conductivity of the CNT sample. These results demonstrate chemical selectivity of CNTs due to varying electronic interaction with different chemical analytes.

Structural health monitoring of aerospace structural components using wave propagation based diagnostics

The paper discusses a wave propagation based method for identifying the damages in an aircraft built up structural component such as delamination and skin-stiffener debonding. First, a spectral finite element mode l (SFEM) is developed for modeling wave propagation in general built-up structures by using the concept of assembling 2D spectral plate elements. The developed numerical model is validated using conventional 2-D FEM. Studies are performed to capture the mode coupling,that is, the flexural-axial coupling present in the wave responses. Lastly, the damages in these built up structures are then identified using the developed SFEM model and the measured responses using the concept Damage Force Indicator (DFI) technique.

Biased PN based impact angle constrained guidance using a nonlinear engagement model

Impact angle constrained guidance laws are important in many applications such as guidance of torpedoes, anti-ballistic missiles and reentry vehicles. In this paper, we design a guidance law which is capable of achieving a wide range of impact angles. Biased proportional navigation guidance uses a bias term in addition to the basic PN command to satisfy additional constraints. Angle constrained BPNG (ACBPNG) uses small angle approximations to derive the bias term for impact angle requirement. We design a modified ACBPNG (MACBPNG) where the required bias term is derived in a closed form considering non-linear equations of motion. Simulations are carried out for a wide range of impact angle requirements. We also analyze capturability from different initial positions and also the launch angles possible at each initial position. The performance of the proposed law is compared with an existing law.

Lamb Wave Propagation in Laminated Composite Structures

Damage detection using guided Lamb waves is an important tool in Structural health Monitoring. In this paper, we outline a method of obtaining Lamb wave modes in composite structures using two dimensional Spectral Finite Elements. Using this approach, Lamb wave dispersion curves are obtained for laminated composite structures with different fibre orientation. These propagating Lamb wave modes are pictorially captured using tone burst signal.

Nonlinear and linear autopilot performance comparison of tactical flight vehicle

n this paper, three-axis autopilot of a tactical flight vehicle has been designed for surface to air application. Both nonlinear and linear design synthesis and analysis have been carried out pertaining to present flight vehicle. Lateral autopilot performance has been compared by tracking lateral acceleration components along yaw and pitch plane at higher angles of attack in presence of side force and aerodynamic nonlinearity. The nonlinear lateral autopilot design is based on dynamic inversion and time scale separation principle. The linear lateral autopilot design is based on three-loop topology. Roll autopilot robustness performance has been enhanced against unmodeled roll disturbances by backstepping technique. Complete performance comparison results of both nonlinear and linear controller based on six degrees of freedom simulation along with stability and robustness studies with respect to plant parameter variation have been discussed in the paper.

Projection Error Propagation-based Regularization (PEPR) method for resistivity reconstruction in Electrical Impedance Tomography (EIT)

A novel Projection Error Propagation-based Regularization (PEPR) method is proposed to improve the image quality in Electrical Impedance Tomography (EIT). PEPR method defines the regularization parameter as a function of the projection error developed by difference between experimental measurements and calculated data. The regularization parameter in the reconstruction algorithm gets modified automatically according to the noise level in measured data and ill-posedness of the Hessian matrix. Resistivity imaging of practical phantoms in a Model Based Iterative Image Reconstruction (MoBIIR) algorithm as well as with Electrical Impedance Diffuse Optical Reconstruction Software (EIDORS) with PEPR. The effect of PEPR method is also studied with phantoms with different configurations and with different current injection methods. All the resistivity images reconstructed with PEPR method are compared with the single step regularization (STR) and Modified Levenberg Regularization (LMR) techniques. The results show that, the PEPR technique reduces the projection error and solution error in each iterations both for simulated and experimental data in both the algorithms and improves the reconstructed images with better contrast to noise ratio (CNR), percentage of contrast recovery (PCR), coefficient of contrast (COC) and diametric resistivity profile (DRP). (C) 2013 Elsevier Ltd. All rights reserved.

Closed-form nonlinear sectional analysis of pretwisted anisotropic beam with multiple delaminations

Fiber reinforced laminated composite open-section beams are widely used as bearingless rotor flex beams because of their high specific strength and stiffness as well as fatigue life. These laminated composite structures exhibit a number of different failure modes, including fiber-matrix debonding within individual layers, delamination or separation of the layers, transverse cracks through one or more layers and fiber fracture. Delamination is a predominant failure mode in continuous fiber reinforced laminated composites and often initiate near the free edges of the structure. The appearance of delaminations in the composite rotorcraft flexbeams can lead to deterioration of the mechanical properties and, in turn, the helicopter performance as well as safety. Understanding and predicting the influence of free-edge delamination on the overall behavior of the laminates will provide quantitative measures of the extent of the damage and help ensure their damage tolerance.

A Kushner-Stratonovich Monte Carlo filter applied to nonlinear dynamical system identification

A Monte Carlo filter, based on the idea of averaging over characteristics and fashioned after a particle-based time-discretized approximation to the Kushner-Stratonovich (KS) nonlinear filtering equation, is proposed. A key aspect of the new filter is the gain-like additive update, designed to approximate the innovation integral in the KS equation and implemented through an annealing-type iterative procedure, which is aimed at rendering the innovation (observation prediction mismatch) for a given time-step to a zero-mean Brownian increment corresponding to the measurement noise. This may be contrasted with the weight-based multiplicative updates in most particle filters that are known to precipitate the numerical problem of weight collapse within a finite-ensemble setting. A study to estimate the a-priori error bounds in the proposed scheme is undertaken. The numerical evidence, presently gathered from the assessed performance of the proposed and a few other competing filters on a class of nonlinear dynamic system identification and target tracking problems, is suggestive of the remarkably improved convergence and accuracy of the new filter. (C) 2013 Elsevier B.V. All rights reserved.