Adaptive Array Beamforming Using a Chaotic Beamforming Algorithm

Jovanović, Ana; Lazović, Luka; Rubežić, Vesna

doi:10.1155/2016/8354204

Cited by 14 publications

(29 citation statements)

References 18 publications

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“…COA is a very powerful optimization technique that has found numerous scientific applications [59][60][61][62][63]. This approach is based on the theory of chaos, which is, in a mathematical sense, described by ordinary differential equations or by an iterative map [64].…”

Section: Coa and Objective Functionmentioning

confidence: 99%

“…Different chaotic systems, including the logistic map, lozi map, tent map and Lorenz system, can be found in the literature. In this paper, we will base COA on the logistic map [59][60][61][62][63][64].…”

Section: Coa and Objective Functionmentioning

confidence: 99%

“…Recently, COA has been used in solving various optimization problems: parameter identification of Jiles-Atherton hysteresis model [59], single-phase transformer parameter estimation [60], design of PID parameters for automatic voltage regulation of synchronous machine [61], antenna array radiation pattern synthesis [62,63]. The main advantages of COA over other optimization techniques are easy implementation and short execution time [64].…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Single-Diode and Two-Diode Solar Cell Parameters by Using a Chaotic Optimization Approach

et al. 2019

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Estimation of single-diode and two-diode solar cell parameters by using chaotic optimization approach (COA) is addressed. The proposed approach is based on the use of experimentally determined current-voltage (I-V) characteristics. It outperforms a large number of other techniques in terms of average error between the measured and the estimated I-V values, as well as of time complexity. Implementation of the proposed approach on the I-V curves measured in laboratory environment for different values of solar irradiation and temperature prove its applicability in terms of accuracy, effectiveness and the ease of implementation for a wide range of practical environment conditions. The COA-based parameter estimation is, therefore, useful for PV power converter designers who require fast and accurate model for PV cell/module.

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Section: Coa and Objective Functionmentioning

confidence: 99%

Section: Coa and Objective Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of Single-Diode and Two-Diode Solar Cell Parameters by Using a Chaotic Optimization Approach

et al. 2019

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“…The effectiveness of the proposed technique will be evaluated through its application on different transformers (different with respect to machine power and voltage levels) found in the literature and in laboratory environment. COA has found application in various optimization techniques [19][20][21]. In [19], COA is successfully applied for parameter identification of Jiles-Atherton hysteresis model.…”

Section: Introductionmentioning

confidence: 99%

“…Design of PID parameters for automatic voltage regulation of synchronous machine by using COA is presented in [20]. In [21], the usage of the chaotic beamforming adaptive algorithm for antenna array's radiation pattern synthesis is presented. In addition, chaos is used to improve the existing heuristic optimization techniques [22,23].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Equivalent Circuit Parameters of Single-Phase Transformer by Using Chaotic Optimization Approach

et al. 2019

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This paper deals with parameter estimation of single-phase transformer equivalent circuit by using Chaotic Optimization Approach (COA). Unknown transformer equivalent circuit parameters need to be accurately estimated for the best possible matching between the measured and the estimated transformer output characteristics (for example, output power—load resistance characteristic). Unlike literature approaches which apply different estimation techniques and are based either on the nameplate data or the load data obtained from experiments, in this paper the use of COA is evaluated on both types of input data. For two single-phase transformers, different with respect to machine power and voltage levels, the COA-based parameter estimation is compared to various literature techniques as well as to classical method based on open-circuit and short-circuit tests. The results show that COA outperforms other approaches in terms of average error between the measured and the estimated values of the primary current, secondary current and secondary voltage at full load, or between the measured and the estimated output characteristics. The effectiveness of COA is additionally confirmed through its application on laboratory 2kVA, 220 V/110 V, 50 Hz single-phase transformer.

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Reconfigurable method of smart antenna beam shaping in indoor fading environment using adaptive algorithms: An exhaustive experimental study

Imtiaj

Bhattacharya

Misra

2020

Int J RF Microw Comput Aided Eng

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Adaptive algorithms for beam shaping of a phased array antenna and multiple-input multiple-output (MIMO) system gaining importance in today's advanced wireless networks to mitigate interference effects and distortion in the receiving signal due to multipath, small scale, and large scale fading effects. This article deals with the development of reconfigurable field programmable gate array (FPGA)-based hardware for smart antenna system to explore parameter dependencies, drawbacks, and relative performance comparison of popular adaptive beamforming and interference suppression algorithms. These are least mean square, recursive least squares (RLS), and sample matrix inversion (SMI) used in real-time under laboratory environment where the existing wireless channel between transmitters and receivers is linear timevarying in nature due to presence of secondary sources giving rise to smallscale fading. For this at first, we propose a novel received signal strength indicator-based procedure to measure the radiation pattern of the antenna under an echoic indoor environment on a reconfigurable and portable FPGA system named wireless open-access research platform (WARP), controllable by generic programming codes over a user-friendly MATLAB interface. For better performance, the SMI algorithm was modified to increase block size rather than block shifting in general SMI. Later a comparative study was performed under varying conditions to observe the best utilization of three adaptive algorithms in beam shaping. In all cases, SMI performs the best with less beam shaping error and faster convergence, validating its use in a real-time fading environment.

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Adaptive Array Beamforming Using a Chaotic Beamforming Algorithm

Cited by 14 publications

References 18 publications

Estimation of Single-Diode and Two-Diode Solar Cell Parameters by Using a Chaotic Optimization Approach

Estimation of Single-Diode and Two-Diode Solar Cell Parameters by Using a Chaotic Optimization Approach

Estimation of Equivalent Circuit Parameters of Single-Phase Transformer by Using Chaotic Optimization Approach

Reconfigurable method of smart antenna beam shaping in indoor fading environment using adaptive algorithms: An exhaustive experimental study

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