Stable neurovisual servoing for robot manipulators

In this paper, we propose a stable neurovisual servoing algorithm for set-point control of planar robot manipulators in a fixed-camera configuration an show that all the closed-loop signals are uniformly ultimately bounded (UUB) and converge exponentially to a small compact set. We assume that the gravity term and Jacobian matrix are unknown. Radial basis function neural networks (RBFNNs) with online real-time learning are proposed for compensating both gravitational forces and errors in the robot Jacobian matrix. The learning rule for updating the neural network weights, similar to a back propagation algorithm, is obtained from a Lyapunov stability analysis. Experimental results on a two degrees of freedom manipulator are presented to evaluate the proposed controller.     

Surface acoustic wave gas sensor of the sorption type sensitive to the thermal properties of gases

The basic principles of a new surface acoustic wave (SAW) gas sensor are described. Being essentially a sensor of the sorption type, the proposed device possesses certain features of the thermometric SAW sensors and is not only sensitive to the vapors of volatile substances, but capable of detecting gases by their thermal properties as well. In contrast to the known thermometric SAW sensors, the proposed sensor is characterized by high temperature stability and fast response. A variant of the sensor based on a LiNbO₃ SAW delay line is described and some results of the test for detecting propane-butane mixtures are presented.     

Pulse-Frequency Characteristics in Bifurcation Problems

Generation of self-oscillations under unstable stationary states of nonlinear control systems, which may contain delay of complicated nature (the Andronov–Hopf bifurcation), and approximate design of self-oscillating states and their asymptotes are studied with the help of pulse-frequency characteristics of the linear component of a system.     

New phenomena in barbotage and sedimentation in magnetic fluids

New multivelocity model was deduced for a dispersive magnetizable medium: magnetic fluid - gas bubbles or solid particles. Resulting equations may be used for discribing the processes of concentration, separation and barbotage. The characteristics of deduced set were examined. The problem was solved concerning floatation and sedimentation of particles or babbles in a magnetic fluid in a solenoidal magnetic field.     

Correlation analysis of geothermal data in North America

Correlation studies of the geothermal parameters have been carried out for Michigan Basin and the results are interpreted with the help of observed relations between heat flow, geological age and crustal thickness for North America. Heat flow and geothermal gradient are found to decrease with thermal conductivity, while they are positively correlated with each other, supporting the earlier findings of Negi et al. (1974). It is noted that, to some extent, these associations can be explained with the help of variations in crustal thickness.     

Tunable circular patch antennas

A method to control the resonant or operating frequencies of circular patch antennas has been investigated experimentally and theoretically. It consists of the placement of passive metallic or tuning posts at approximate locations within the input region of the antenna. Comparison of measured and analytical results seems to establish the validity of a theoretical model proposed to determine the input performance of such circular patch antennas.     

Fuzzy sets based knowledge systems and knowledge elicitation

Fuzzy sets are adequate forms of knowledge representation when the information is uncertain due to vagueness and imprecision. Knowledge structures using fuzzy sets are similar to those implemented in non-fuzzy systems. Classical knowledge elicitation methods can be used in combination with techniques to develop membership functions. The fuzzy set representation has several advantages, including flexibility in expressing uncertain knowledge during elicitation, representation of the knowledge and its uncertainty as a unique entity, easy interfacing with classical systems, and a more robust system in ill-defined domains. These advantages result in increased system reliability.