Invasive Weed Optimization (IWO) Algorithm for Control of Nulls and Sidelobes in a Concentric Circular Antenna Array (CCAA)

Abstract

The ever increasing wireless communication research is giving rise to a plethora of new communication techniques. There is also a wide spread increase in the use of existing systems such as mobiles, Wi-Fi, RADARS, Space communications etc. Consequently, the electromagnetic spectrum is getting overcrowded and there is an increase in interference due to use of multiple devices with in a small cluster. So, design of antennas with small sidelobe levels and nulls in interference direction is needed. This paper illustrates the procedure for placing nulls in the interference direction while reducing sidelobe level (SLL) of a CCAA under the constraint of fixed FNBW (as in the case of uniform excitation). IWO is used to find the excitation amplitudes of a three ring CCAA that satisfy the desired goal better. Three design examples are provided. IWO is more robust and efficient algorithm than GA, PSO and Simulated Annealing etc.

Design of (FPID) controller for Automatic Voltage Regulator using Differential Evolution Algorithm

“…the most steps of the de rule ar, initialization, Evaluation, Repeat, Mutation, Recombination, Evaluation ,Selection, till (termination criteria are met).The block-diagram of DE is shown in Fig. For comparison DE algorithm with other optimization techniques (IWO),(SCA), and because the paper size limitation, all these techniques are not considered in detail, so that ,for (IWO) refer to Ref [25],and let the parameters of algorithm are:-Varmin=[0 0 0 0 0],Varmax=[ 10 10 1.5 10 1.5], maximum number of iterations=150, initial population size=2,maximum population size=10,minimum number of seeds=0,maximum number of seeds=5, variance reduction exponent=2,initial value of standard deviation=0.5 and final value of standard deviation=0.001.Table 4. indicates the FPID controller values depending on the performance index.…”