Robust optimum design of SAW filters with the Taguchi method and a memetic algorithm

This paper presents a robust optimum design approach to tackle the structural design of surface acoustic wave (SAW) filters. The frequency response characteristics of SAW filters are governed primarily by their geometrical structures: the configurations of inter-digital transducers (IDTs) and grating reflectors fabricated on piezoelectric substrates. For deciding an optimal structure of SAW filters based on the computer simulation, the equivalent circuit model of IDT, which includes several uncertain parameters, has to be utilized. In order to cope well with the designing imperfections caused by the inevitable dispersion of these uncertain parameters, the quality engineering technique, or the Taguchi method, is employed. First of all, according to the Taguchi method, the signal to noise ratio (SNR) of SAW filters is defined to evaluate their robustness. Then, for increasing the SNR of SAW filters as much as possible without losing their specified functions, the robust optimum design of SAW filters is formulated as a constrained optimization problem. Furthermore, a memetic algorithm combining an evolutionary algorithm based on the penalty function method with a local search is proposed. Finally, the memetic algorithm is effectively applied to the robust optimum design of a resonator type SAW filter. Computational experiments show that the proposed memetic algorithm not only can find a feasible solution of the constrained optimization problem, or a desirable structure of objective SAW filter, but also can drastically improve the robustness of the SAW filter.