The Chaotic beamforming adaptive algorithm is new adaptive method for antenna array’s radiation pattern synthesis. This adaptive method based on the optimization of the Least Mean Square algorithm using Chaos theory enables fast adaptation of antenna array radiation pattern, reduction of the noisy reference signal’s impact, and the improvement of the tracking capabilities. We performed simulations for linear and circular antenna arrays. We also compared the performances of the used and existing algorithms in terms of the radiation pattern comparison.
Purpose
The purpose of this paper is to propose a chaotic optimization method for identifying the parameters of the Jiles–Atherton (J-A) hysteresis model.
Design/methodology/approach
The J-A model has five parameters which are assigned with physical meaning and whose determination is demanding. To determine these parameters, the fitness function, which represents the difference between the measured and the modeled hysteresis loop, is formed. Optimal parameter values are the values that minimize the fitness function.
Findings
The parameters of J-A model for three magnetic materials are determined. The model with the optimal parameters is validated using measured data and comparison with particle swarm optimization algorithm, genetic algorithm, pattern search and simulated annealing algorithm. The results show that the proposed method provides better agreement between measured and modeled hysteresis loop than other methods used for comparison. The proposed method is also suitable for simultaneous optimization of multiple hysteresis loops.
Originality/value
Chaotic optimization method is implemented for the first time for J-A model parameter identification. Numerical comparisons with results obtained with other optimization algorithms demonstrate that this method is a suitable alternative in parameters identification of J-A hysteresis model. Furthermore, this method is easy to implement and set up.
Purpose
The purpose of this paper is to use the proposed algorithm for the fast adaptation of the antenna array radiation pattern on the particular scenario of the incoming signals. The fitness function to be minimized includes the precise estimation of signals’ arrival angles, setting the deep nulls in the directions of the interfering signal, the reduction of the main lobe’s width and the reduction of side lobes.
Design/methodology/approach
Unlike conventional adaptive algorithms, the proposed algorithm allows synthesis of radiation patterns in the case of a larger number of incident desired and interfering signals. The proposed method also reduces the width of the dead zone.
Findings
In this paper a comparison of the results obtained from the chaotic beamforming algorithm with the results obtained by using the Sequential Quadratic Programming method is presented.
Originality/value
The chaotic beamforming algorithm is proposed here. It is based on the optimization of the least mean square and on the variable step-size least mean square algorithms, using chaos theory for synthesis of the radiation pattern of the linear antenna array.
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