Quantum Based Particle Swarm Optimization for Equivalent Circuit Design of Terminal Antenna Impedance

In this paper, an improved quantum-behaved particle swarm optimization (QPSO) approach for modeling antenna impedance is illustrated. In the proposed study, the enhanced weighted quantum particles swarm optimization (EWQPSO) is introduced with the aim to achieve local convergence acting on a reduced number of free parameters. To verify the performance of the proposed EWQPSO, several tests involving Ipersphere, Alpine, De Jong, Zakharov, Salomon functions were carried out. The obtained results demonstrated that the convergence is achieved more quickly by the EWPSO than other optimization algorithms based on QPSO. A lumped element equivalent circuit was designed to model the terminal impedance of a broadband planar sinuous antenna in the frequency range from 1 to 3 GHz. The developed EWQPSO algorithm is then used to recover all the parameters characterizing the equivalent circuit. The resulting circuit exhibited a good impedance fidelity over the whole frequency range.

Automated summary

This paper illustrates an improved quantum-behaved particle swarm optimization (QPSO) approach for modeling antenna impedance. The introduced enhanced weighted quantum particles swarm optimization (EWQPSO) achieves local convergence on a reduced number of free parameters. Several tests were conducted to verify the performance of the proposed EWQPSO, showing that it achieves faster convergence compared to other QPSO-based optimization algorithms. A lumped element equivalent circuit was designed and the developed EWQPSO algorithm successfully recovered all the parameters characterizing the circuit, resulting in good impedance fidelity over the whole frequency range.