Investigation of Simulated Annealing, Ant-Colony Optimization, and Genetic Algorithms for Self-Structuring Antennas

Coleman, C.M.; Rothwell, Edward J.; Ross, John E.

doi:10.1109/tap.2004.825658

Cited by 118 publications

(46 citation statements)

References 12 publications

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“…It is easy to see how the value of s n,t influences the solution construction step. A large pheromone width results in drastic changes in solution component, whereas a small pheromone width results in small changes, that is, solution components that differ very little from already explored ones [10]. This behaviour is analogue to the temperature parameter in simulated annealing class algorithms.…”

Section: Radiation Pattern Optimisation -Acomentioning

confidence: 96%

“…Optimisation algorithms relying on natural principles, such as ACO and Particle Swarm Optimisation [9], are powerful methods that can be implemented in electromagnetic applications. Whereas the behaviour of individual ants is subject to a few basic rules, the collective behaviour exhibits highly intelligent and organised properties [10]. This is evident in the food foraging behaviour of real-life ant colonies.…”

Section: Radiation Pattern Optimisation -Acomentioning

confidence: 99%

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Ant Colony Optimisation-based radiation pattern manipulation algorithm for Electronically Steerable Array Radiator Antennas

Aelterman

Goossens

Declercq

et al. 2009

IET Sci. Meas. Technol.

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A new algorithm for manipulating the radiation pattern of Electronically Steerable Array Radiator Antennas is proposed. A continuous implementation of the Ant Colony Optimisation (ACO) technique calculates the optimal impedance values of reactances loading different parasitic radiators placed in a circle around a centre antenna. By proposing a method to obtain a suitable sampling frequency of the radiation pattern for use in the optimisation algorithm and by transforming the reactance search space into the search space of associated phases, special care was taken to create a fast and reliable implementation, resulting in an approach that is suitable for real-time implementation. The authors compare their approach to analytical techniques and optimisation algorithms for calculating these reactances. Results show that the method is able to calculate near-optimal solutions for gain optimisation and side lobe reduction.

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Section: Radiation Pattern Optimisation -Acomentioning

confidence: 96%

Section: Radiation Pattern Optimisation -Acomentioning

confidence: 99%

Ant Colony Optimisation-based radiation pattern manipulation algorithm for Electronically Steerable Array Radiator Antennas

Aelterman

Goossens

Declercq

et al. 2009

IET Sci. Meas. Technol.

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show abstract

“…The adaptive algorithm that modifies the impedance matching network must be customised to the type of impedance matching circuit deployed. Some papers [17,18] propose a discrete impedance matching network, consisting of a bank of capacitors or inductors, together with global optimisation algorithms such as the genetic algorithm, simulated annealing or the ant colony optimisation [19]. However, this setup occupies a lot of space, which may not be available on a commercial life-jacket.…”

Section: Iet Microwaves Antennas and Propagationmentioning

confidence: 99%

Wearable self‐tuning antenna for emergency rescue operations

Baroni

Nepa

Rogier

2016

IET Microwaves, Antennas & Propagation

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In this study, the design, hardware implementation and characterisation of a self-tuning 406 MHz antenna of a Cospas-Sarsat personal locator beacon are presented. The realised prototype is able to perform automatic tuning of the antenna under time-varying environmental conditions due to human body movements and sea water proximity. The impedance tuning is performed by tracking the instantaneous value of the reflection coefficient and by modifying an appropriate impedance matching network according to a real-time adaptive algorithm. A resilient default/backup software architecture has been designed to ensure that tuning guarantees a return loss higher than 10 dB for the personal locator beacon in most of impedance mismatching conditions.

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“…This algorithm is based on the behavior of ant colonies when they are looking for food and storing it in their nests. ACO has been very rarely used to solve electromagnetic problems (Coleman et al (2004), Quevedo-Teruel & Rajo-Iglesias (2006), ), however its characteristics could be interesting for this purpose in some situations as it will be shown along this chapter.…”

Section: Algorithm Descriptionmentioning

confidence: 99%