Design of load-ended spiral antennas for RFID UHF passive tags using improved artificial bee colony algorithm
In this paper, new planar spiral antennas for passive RFID tag application at UHF band are designed and optimized using a new artificial bee colony (ABC) algorithm. We apply the improved ABC (I-ABC), which is an improved version of the original ABC algorithm. The I-ABC introduces the best-so-far solution, inertia weight and acceleration coefficients to modify the search process. The optimization goals are antenna size minimization, gain maximization and conjugate matching. The antenna dimensions were optimized and evaluated using I-ABC in conjunction with commercial EM software. We compare the I-ABC with the original ABC algorithm. The obtained results show that both algorithms are powerful optimizers that can be efficiently applied to tag antenna design problems. I-ABC produces better results than the original ABC algorithm in terms of solution accuracy and success rate. RFID tags with dimensions less than 3cm, maximum gain that reaches the value of 1.46dBi and read distance more than 10m were among those obtained by the algorithm.
rfid tag design optimization methods evolutionary algorithms swarm intelligence artificial bee colony optimization