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Eye tracking devices have been extensively used to study human selection mechanisms and promoted the development of computational models of visual attention, whose well known outcomes are the saliency maps. Among the eye trackers, wearable ones have the advantages of allowing the estimation of the Point of Regard (POR) while performing natural tasks, instead of experimental, static lab settings. The motion of the viewer makes localization necessary to collect data in a coherent reference frame. In this work we present a framework for the estimation and mapping of the sequence of 3D PORs collected by a wearable device in unstructured, experimental settings. The result is a three-dimensional map of gazed objects, which we call 3D Saliency Map and constitutes the novel contribution of this work.

Nowadays, many countries like to decrease their dependency on oil especially in energy generation. Fuel cell energy generation system is one of the most exiting techniques that have many advantages such as being clean, reliable, oil independent, ozone friendly, vibration free, movable and having high efficiency. For ensuring fuel cells correct operation, it is surrounded by many ancillary circuits which consume about 40% of its energy product. About 30% of this consumed energy uses by compressor which provides required air of system. Because of that, it seems wise to control and optimize the performance of compressor to maximize the output energy of system. Generally, compressors do not have any analytical formula, so their performance models by some characteristic charts or empirical formulas. Therefore, in controlling compressors, using model-based controllers may causes error and not be useful. In this case, fuzzy logic controller which is more robust than other conventional controllers can be good candidate. In this study, three fuzzy logic controllers are designed for controlling compressor performance. Matlab/Simulink toolbox is used to simulate system and study the accuracy and correctness of the system. The results show good accuracy of the designed controllers.

Main purpose of the study presented in this papers is to demonstrate the fuzzy logic control design by singular perturbation approach for trajectory tracking of two cooperating planar rigid robots handling a flexible beam which does not require any vibration measurement of the beam. First, kinematics and dynamics of the robots and the object are derived. Then, using the relations between different forces acting on the object by the manipulators' end-effectors, the dynamic equations of the robots and the object are combined. Applying two-time scale control theory on the combined dynamics, a control scheme is elaborated which makes the position and orientation of the mass center of the beam track a desired trajectory while suppressing the beam vibration. In the proposed controller, fast (flexible) subsystem controller will damp out the vibration of the flexible beam by an optimal design and the other slow (rigid) subsystem fuzzy controller dominates the trajectory tracking. These two controllers constitute the composite control scheme. To avoid requiring any beam vibration measurement for the fast control law, a linear time-variant observer is also designed. A computer was utilized as a simulation tool; the simulation results show the control method is robust and quite effective in performance.

The paper presents an approach to power system state estimation based on the application of fuzzy logic. Significant improvements in state estimates are achieved (relative to the weighted least squares algorithm) by using a hybrid estimator incorporating fuzzy logic concepts. The design of the fuzzy estimator is described. The approach is illustrated for two sample systems: a 6-bus and a 30-bus system.