A compact planar multiband antenna operating at 3.1 (S-band) /4.7/6.4/7.6 (C-band) /8.9/10.4/11.8 GHz (X-band) is presented. The proposed Microstrip Patch Antenna (MSPA) consists of a rectangular radiator in which an E-shaped slot is etched out and a microstrip feed line. The E-shaped slot modifies the total current path thereby making the antenna to operate at seven useful bands. No external impedance matching circuit is used and the impedance matching at these bands are solely achieved by using a rectangular microstrip feed line of length 10mm (L6) and width 2mm (W10). The antenna has a compact dimension of ���� × ���� × ��. �� ������ and exhibits S11<-10dB bandwidth of about 6.45% (3.2-3.0GHz), 8.5% (4.9-4.5GHz), 7.6% (6.7-6.2GHz), 3.9% (7.8-7.5GHz), 5.7% (9.1-8.6GHz), 1.2% (10.44-10.35GHz) and 2.2% (11.87-11.62GHz). The simulation analysis of the antenna is carried out by using HFSS v.13.0.

A comparative analysis of a compact planar Square patch Microstrip Multiband antenna on three different substrates is proposed. The proposed design has a C-shaped slot etched on the square radiating part and the antenna is energized using microstrip feed line. RT Duroid (ε _r= 2.2), Taconic (ε _r= 3.2) and FR4 (ε _r= 4.4) substrates are used for simulation analysis. The flow of current is modified by the C-shaped slot making the antenna to resonate at 3/4 and 6 bands for RT Duroid/Taconic and FR4 substrates respectively suitable for 5G sub GHz applications. The antenna has a compact dimension of 32 × 32 × 1.6 mm ³ and exhibits a return loss, S11 of less than -10dB for all the resonating frequencies for all three substrates. The analysis has been done by considering the S11 (Return loss <-10 dB), Directivity, Antenna Gain, VSWR and surface current distribution. Table II provides the comparison of parameters for different substrate material.

A compact Sierpinski Carpet square fractal multiband antenna operating at 3.9 (WiMAX) /6.6 (Satellite TV) /8.1/10.7/11.8 GHz (X-band) is presented. The proposed Microstrip Patch Antenna (MSPA) consists of a Sierpinski Carpet square fractal radiator in which square slots are etched out and a tapered microstrip feed line. The Sierpinski Carpet square fractal patch modifies the current resonant path thereby making the antenna to operate at five useful bands. Impedance matching at these bands are solely achieved by using Sierpinski square slot and tapered feedline, thus eliminating the need of any external matching circuit. The dimensions of the compact antenna is 32 x 32 x 1,6 mm3 and exhibits S11<-10dB bandwidth of about 4.8% (4.01-3.82 GHz), 2.1% (6.62-6.48 GHz), 2.7% (8.24-8.02 GHz), 2.1% (10.77-10.54 GHz) and 21% (12.1-11.60 GHz) with the gain of 7.57/3.91/3.77/6.74/1.33 dB at the operating frequencies 3.9/6.6/8.1/10.7 and 11.8 GHz, respectively under simulation analysis carried out by using HFSS v.13.0.

The wind energy conversion systems (WECS) suffer from an intermittent nature of source (wind) and the resulting disparity between power generation and electricity demand. Thus, WECS are required to be operated at maximum power point (MPP). This research paper addresses a sophisticated MPP tracking (MPPT) strategy to ensure optimum (maximum) power out of the WECS despite environmental (wind) variations. This study considers a WECS (fixed pitch, 3KW, variable speed) coupled with a permanent magnet synchronous generator (PMSG) and proposes three sliding mode control (SMC) based MPPT schemes, a conventional first order SMC (FOSMC), an integral back-stepping-based SMC (IBSMC) and a super-twisting reachability-based SMC, for maximizing the power output. However, the efficacy of MPPT/control schemes rely on availability of system parameters especially, uncertain/nonlinear dynamics and aerodynamic terms, which are not commonly accessible in practice. As a remedy, an off-line artificial function-fitting neural network (ANN) based on Levenberg-Marquardt algorithm is employed to enhance the performance and robustness of MPPT/control scheme by effectively imitating the uncertain/nonlinear drift terms in the control input pathways. Furthermore, the speed and missing derivative of a generator shaft are determined using a high-gain observer (HGO). Finally, a comparison is made among the stated strategies subjected to stochastic and deterministic wind speed profiles. Extensive MATLAB/Simulink simulations assess the effectiveness of the suggested approaches.