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A compact triple band antenna with stacked T-shaped strips inside a rectangular ring monopole has been proposed. This novel structure with a slot in the defected ground achieves triple band opration i.e. 2.47–2.77 GHz, 3.3–3.7 GHz and 5.10–6.62 GHz. These bands find application in important wireless communication standards like WiMAX (3.3–3.8 GHz, and 5.25–5.85 GHz, WLAN (2.4 G-2.5 GHz, 5.1–5.3 GHz, and 5.72–5.85 GHz). The antenna is printed on a FR-4 substrate with an overall dimension of $$33 \times 17 \times 1.6 \;{\text{mm}}^{3}$$ 33 × 17 × 1.6 mm 3 . An impedance bandwidth of 11% (2.47–2.77 GHz), 11% (3.3–3.7 GHz) and 25% (5.10–6.62 GHz) is obtained. A good conjunction between the simulated and measured results is inferred from the antenna design analysis.

Operating wind power generation system at optimal power point is essential which is achieved by employing a Maximum Power Point Tracking (MPPT) control strategy. This literature focuses on developing a novel particle swarm optimization algorithm enhanced radial basis function neural network supported TSR based MPPT control strategy for Doubly Fed Induction Generator (DFIG) based wind power generation system. The proposed hybrid MPPT control strategy estimates the effective wind speed and estimates the optimal rotor speed of the wind power generation system to track the maximum power. The proposed controller extremely reduces the speed dissimilarity range of wind power generation system, which leads to rationalizing the pulse width inflection of DFIG rotor side converter. This in turn, increases the system's reliability and delivers an effective power tracking with reduced converter losses. Furthermore, by utilizing the proposed MPPT controller, the converter size can be reduced to 40%. Therefore, the overall cost of the system can be gradually decreased. To validate the performance of the proposed MPPT controller, an extensive simulation study has been carried out under medium and high wind speed conditions in MATLAB/Simulink. The obtained results have been justified using experimental analysis.

Torque ripple and harmonics in permanent magnet synchronous motor (PMSM) cause negative impacts on its speed control and overall efficiency. In this article, an Elman neural network (ENN)-controlled feedback linearization-based direct torque control strategy has been proposed to mitigate torque ripples and undesirable harmonics of PMSM. In this approach, the stator flux, stator flux position, and developed torque are used to generate a switching pulse to the impedance source inverter employing ENN controller. By changing the switching pattern of the impedance source inverter through modifying the pulse width modulation using the proposed control strategy. It is possible to control the armature current of the PMSM at various orders and corresponding time harmonics under different operating conditions. The outstanding aspect of the proposed control strategy is that it boosts the inverter operation and reduces the requirement of the DC-DC converter in boosting. For evaluating the performance of the developed control strategy, an extensive simulation study has been conducted in the MATLAB/Simulink environment, and experimental analysis is carried out using the Xilinx-FPGA kit.