By Adrian Olaru
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Additional info for Biomechanics, Neurorehabilitation, Mechanical Engineering, Manufacturing Systems, Robotics and Aerospace
1094 . , Olaru, A. (2008). 143- 152, ISBN 978-973-648-784-2, Predeal, may 2008, Bren, Bucharest. , Olaru, S. (2006). , pp. 73- 81, ISBN 978-83-89334-49-7, Bydgoszcz, nov. 2006, Akademia Techniczno-Rolnicza, Bydgoszcz. ro Keywords: auto-pilot, modelling paramethers, flight parameters. Abstract: the work paper presents the auto-pilot solution adopted for an unconventional unmanned air vehicle (EADFP - unmanned aerial hybrid baloon-copter system) based on a simplified algorithm implemented on a micro-controller hardware configuration.
In fact, each pair of scene temperatures (1, 2), (3, 4), (5, 6), (7, 8) have different pairs of integration time and gain (tINT 1, G1 ), (tINT2, G2 ), (tINT 3, G3 ), (tINT 4, G4 ). Time integration value is limited by the frame rate of the system in use and starting from its working possibilities one can fix the integration time at a suitable value and then increase the gain value until the desired well fill capacity. 4 ms). For example, if a value of 28,5 time integration is too much (in point 2 of figure 6), one can fix it at 7 ms and increases the gain value at 6 (2,7 V /0,46 V) to obtain a 90% well fill capacity.
8. All the proper VI-s, designed for these research, works on-line with the possibility to adjusted them to obtain one small errors in the validation research activities, when was compared the simulation modeling with the answer data obtained by data acquisition and experimental research. Some of these results we can see in the last our researches, references [13-18]. The experimental research show how was changed the Fourier spectrum when was applied the proper neural network to the errors between the target data and the acceleration data obtained by acquisition.