Mechanical and electrical driving field induced high-frequency dielectric anomalies in ferroelectric systems

Polycrystalline or single-crystal ferroelectric materials present dielectric dispersion in the frequency range 100 MHz-1 GHz that has been attributed to a dispersive ( relaxation-like) mechanism as well as a resonant mechanism. Particularly in 'normal' ferroelectric materials, a dielectric response that is indistinguishable from dispersion or a resonance has been reported. Nevertheless, the reported results are not conclusive enough to distinguish each mechanism clearly. A detailed study of the dielectric dispersion phenomenon has been carried out in PbTiO3-based ferroelectric ceramics, with the composition Pb1-xLaxTiO3 (x = 0.15), over a wide range of temperatures and frequencies, including microwave frequencies. The dielectric response of La-modified lead titanate ferroelectric ceramics, in 'virgin' and poled states, has been investigated in the temperature and frequency ranges 300-450 K and 1 kHz-2 GHz, respectively. The results revealed that the frequency dependence of the dielectric anomalies, depending on the measuring direction with respect to the orientation of the macroscopic polarization, may be described as a general mechanism related to an 'over-damped' resonant process. Applying either a uniaxial stress along the measurement field direction or a poling electric field parallel and/or perpendicular to the measuring direction, a resonant response of the real and imaginary components of the dielectric constant is observed, in contrast to the dispersion behavior obtained in the absence of the stress, for the 'virgin' samples. Both results, resonance and/or dispersion, can be explained by considering a common mechanism involving a resonant response (damped and/or over-damped) which is strongly affected by a ferroelastic-ferroelectric coupling, contributing to the low-field dielectric constant.

Spin stabilized satellite's attitude analytical prediction

An analytical approach for spin stabilized attitude propagation is presented, considering the coupled effect of the aerodynamic torque and the gravity gradient torque. A spherical coordination system fixed in the satellite is used to locate the satellite spin axis in relation to the terrestrial equatorial system. The spin axis direction is specified by its right ascension and the declination angles and the equation of motion are described by these two angles and the magnitude of the spin velocity. An analytical averaging method is applied to obtain the mean torques over an orbital period. To compute the average components of both aerodynamic torque and the gravity gradient torque in the satellite body frame reference system, an average time in the fast varying orbit element, the mean anomaly, is utilized. Afterwards, the inclusion of such torques on the rotational motion differential equations of spin stabilized satellites yields conditions to derive an analytical solution. The pointing deviation evolution, that is, the deviation between the actual spin axis and the computed spin axis, is also availed. In order to validate the analytical approach, the theory developed has been applied for spin stabilized Brazilian satellite SCD1, which are quite appropriated for verification and comparison of the data generated and processed by the Satellite Control Center of the Brazil National Research Institute (INPE). Numerical simulations performed with data of Brazilian Satellite SCD1 show the period that the analytical solution can be used to the attitude propagation, within the dispersion range of the attitude determination system performance of Satellite Control Center of the Brazilian Research Institute.

Development of a support vector machine-based navigation system for driving a mobile robot through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features. Such features are then submitted to a support vector machine in order to find out the most appropriate route. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route. © 2012 IEEE.

Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science