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The theoretical aspects of a new type of piezo-resistive pressure sensors for environments with rapidly changing temperatures are presented. The idea is that the sensor has two identical diaphragms which have different coefficients of linear thermal expansion. Therefore, when measuring pressure in environments with variable temperature, the diaphragms will have different deflection. This difference can be used to make appropriate correction of the sensor output signal and, thus, to increase accuracy of measurement. Since physical principles of sensors operation enable fast correction of the output signal, the sensor can be used in environments with rapidly changing temperature, which is its essential advantage. The paper presents practical implementation of the proposed theoretical aspects and the results of testing the developed sensor.

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The components of technologies of increasing information and energy efficiency of IoT monitoring networks subscriber systems with protected transfer functioning of reliable packets of information with the increased information capacity are described. In the places of formation of network flows, i.e. in the places of installation of object and on-board systems the realization of a complex of adaptive filtering algorithms, compression and protection of samples of monitoring signals and video data frames with the subsequent adaptive formation and transmission of highly informative code-signal sequences is offered. It is proposed a signal approach as a basis for inputting and compact coding of signals and video data frames of the reliable samples. The signal approach is proposed, according to which the amplitude-time or amplitude-number parameters of the most informative samples of signals and video signals are determined in the rate of input of monitoring data. These are extremes and points of inflection or points of curve movement change. The obtained data are subject to data compression with controlled information loss and lossless compression-protection. According to the proposed information technology for building effective IoT networks for crypto protection of monitoring data arrays by processors of object and on-board systems, the use of disposable ciphers is proposed, which are the rules and parameters for generating crypto-resistant pseudo-random data arrays of a certain length. These rules and parameters are known only to the subscriber-transmitter and the subscriber-receiver of information packets and are used by network subscribers in the process of data compression with losses and without losses, in the process of crypto-resistant and noise-resistant information packets forming of limited duration with increased information capacity. Energy-efficient data packet transmission is based on a significant reduction in the output streams of protected highly informative monitoring data packets and the implementation by object and on-board systems processors a set of algorithms for processing, encoding, encrypting and transmitting data minimized by computational complexity.

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Mostly the dynamics of controlled objects is often described by nonlinear equalizations. Last years themethodology of neural networks is engaged into designing the systems controlling such objects, in particular due to theinfluence of nonlinearities can be taken into account by nonlinear functions of the activation. Such methodology brings someintelligence to the designed system.Authors proposed the purposeful procedure of forming the structure of the neural controller according the desired lawof the control using the discrete transformation of the motion equation. Requirements to the mathematical model of thereference and method of network training are determined, and the control quality is estimated at traditional passing thedisagreement error in the controller input and for the proposed new configuration of its input circuit, namely with separatedinputs. Simulation results confirmed providing the better quality of the system control.DOI: http://dx.doi.org/10.5755/j01.itc.44.3.7717

The piezodrivers are often used in nanopositioning systems. They need very precise and in time operating. The possibility of neural networks ideology for such system controller designing is discussed in this paper.