A novel design of a circuit used for NTC thermistor linearization is proposed. The novelty of the proposed design consists in a specific combination of two linearization circuits, a serial-parallel resistive voltage divider and a two-stage piecewise linear analog-to-digital converter. At the output of the first linearization circuit the quasi-linear voltage is obtained. To remove the residual voltage nonlinearity, the second linearization circuit, i.e., a two-stage piecewise linear analog-to-digital converter is employed. This circuit is composed of two flash analog-to-digital converters. The first analog-to-digital converter is piecewise linear and it is actually performing the linearization, while the second analog-to-digital converter is linear and it is performing the reduction of the quantization error introduced by the first converter. After the linearization is performed, the maximal absolute value of a difference between the measured and real temperatures is 0.014°C for the temperature range between −25 and 75°C, and 0.001°C for the temperature range between 10 and 40°C.

This paper proposes the design and simulation of 2×2 circular patch antenna array working at 28 GHz by using four inset feed micro strip circular patch antennas to achieve beam forming with directivity around 13dB which is required to overcome part of high path loss challenge for high data rate mm-5G mobile station application. Four element 2x2 array consists of two 1x2 circular patch antenna arrays based on power divider and quarter wavelength transition lines as a matching circuit. The designed antenna array is simulated on RT/duroid 5880 dielectric substrate with properties of 0.5mm thickness, dielectric constant ε _r =2.2, and tangent loss of 0.0009 by using Computer System Technology (CST) software. The performances in terms of return loss, 3D–radiation pattern is evaluated at 28 GHz frequency band. The design also includes the possibility of inserting four identical 2x2 antenna arrays at four edges of mobile station substrate to achieve broad space coverage by steering the beams of the mobile station arrays.

As nonlinear optimization techniques are computationally expensive, their usage in the real-time era is constrained. So this is the main challenge for researchers to develop a fast algorithm that is used in real-time computations. This work proposes a fast nonlinear model predictive control approach based on particle swarm optimization for nonlinear optimization with constraints. The suggested algorithm divide and conquer technique improves computing speed and disturbance rejection capability, demonstrating its suitability for real-time applications. The performance of this approach under constraints is validated using a highly nonlinear fast and dynamic real-time inverted pendulum system. The solution presented through work is computationally feasible for smaller sampling times and it gives promising results compared to the state of art PSO algorithm