This paper presents a novel complementary CPWfed slotted microstrip patch antenna for operation at 2.4 GHz, 5.2 GHz and 6.3 GHz frequencies. The primary structure consists of the complementary split ring resonator slots on a patch and the design is fabricated on FR-4 epoxy substrate with substrate thickness of 1.6 mm. The described structure lacks the presence of a ground plane and makes use of a number of circular complementary SRRs along with rectangular slots on the radiating patch. The structure provides a wide bandwidth of around 390 MHz, 470 MHz and 600 MHz at the three bands with return losses of -11.5 dB, -24.3996dB and -24.4226 dB, respectively. The inclusion of the rectangular slots in the CSRR based slot antenna with stairecase structure improved the performance with respect to return loss.

In the paper the parallel compensator considered in [1] is applied to control of the plants with delay and compared with Smith predictor. It is noted that Smith predictor removes only the delay, while the parallel compensator also changes the dynamics of the replacement plant; the latter may be in some degree of freedom shaped by the designer. Owing to this the transients of the system with parallel compensator are significantly faster. Accounting implementability, the control saturations are introduced in control algorithms. Additionally it is shown that using parallel compensator we may apply a relay control to the plants with delay and nonminimum phase zeros, which is impossible by using Smith predictor. Several results of simulations are described which confirm these observations.

The main purpose of the presented research is to investigate the partial discharge (PD) phenomenon variability under long-term AC voltage with particular consideration of the selected physical quantities changes while measured and registered by the acoustic emission method (AE). During the research a PD model source generating surface discharges is immersed in the brand new insulation mineral oil. Acoustic signals generated by the continuously occurred PDs within 168 hours are registered. Several qualitative and quantitative indicators are assigned to describe the PD variability in time. Furthermore, some longterm characteristics of the applied PD model source in mineral oil, are also presented according to acoustic signals emitted by the PD. Finally, various statistical tools are applied for the results analysis and presentation. Despite there are numerous contemporary research papers dealing with long-term PD analysis, such complementary and multiparametric approach has not been presented so far, regarding the presented research. According to the presented research from among all assigned indicators there are discriminated descriptors that could depend on PD long-term duration. On the grounds of the regression models analysis there are discovered trends that potentially allow to apply the results for modeling of the PD variability in time using the acoustic emission method. Subsequently such an approach may potentially support the development and extend the abilities of the diagnostic tools and maintenance policy in electrical power industry.

Covering a wide area by a large number of WiFi networks is anticipated to become very popular with Internet-of-things (IoT) and initiatives such as smart cities. Such network configuration is normally realized through deploying a large number of access points (APs) with overlapped coverage. However, the imbalanced traffic load distribution among different APs affects the energy consumption of a WiFi device if it is associated to a loaded AP. This research work aims at predicting the communication-related energy that shall be consumed by a WiFi device if it transferred some amount of data through a certain selected AP. In this paper, a forecast of the energy consumption is proposed to be obtained using an algorithm that is supported by a mathematical model. Consequently, the proposed algorithm can automatically select the best WiFi network (best AP) that the WiFi device can connect to in order to minimize energy consumption. The proposed algorithm is experimentally validated in a realistic lab setting. The observed performance indicates that the algorithm can provide an accurate forecast to the energy that shall be consumed by a WiFi transceiver in sending some amount of data via a specific AP.