Optimization Design Of Inverted-F Antenna Based On An Improved Tabu Search Method

Due to the development of the computer technology and electromagnetic computation theory,the electromagnetic inverse problem with the background of design for electromagnetic devices and aimed to fulfill the realistic demands of the development of the engineering technology has become the topical subject in the field of electromagnetic application research.Based on the available algorithms for comprehensive analysis and integration,this thesis mainly studies the application of the fast global optimization method to the inverse electromagnetic problem.In view of tabu search algorithm is clear and easy to implement,this thesis focuses on tabu search algorithm(TS).Different improvements are proposed to develop robust optimizers in senses of both convergence speeds and global search abilities,it is the tabu search-Genetic Algorithm(GA)method and the tabu search-Particle Swarm Optimization(PSO)method.Typical mathematic functions are solved to demonstrate the effectiveness and efficiency of the improved TS.Finally,aiming at the existing Inverted-F antenna(IFA),gain deficiencies,high return loss and narrow effective bandwidth,the proposed hybrid algorithms call for HFSS to establish antenna model.The simulation on three structure parameters of Inverted-F antenna(two vertical arm spacing S,antenna height H and resonance length L)is carried out,and the better antenna structure parameters is derived,when2.45 GHz as the center frequency point.The simulation results under the Inverted-F antenna show good radiation performance,whose return loss is as low as Sll=-51.0830 dB and S11=-62.1042 dB.The numerical results of Inverted-F antenna as reported validate the feasibility and the robustness of the corresponding algorithms.