Research of the Robust Optimum Design of Surface Acoustic Wave (SAW) Devices for Mobile and Wireless Communications
| Project/Area Number |
15560348
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
System engineering
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| Research Institution | Kobe University |
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Principal Investigator |
TAGAWA Kiyoharu Kobe University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (50252789)
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| Project Period (FY) |
2003 – 2005
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| Project Status |
Completed (Fiscal Year 2005)
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| Budget Amount *help |
¥1,600,000 (Direct Cost: ¥1,600,000)
Fiscal Year 2005: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2004: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 2003: ¥500,000 (Direct Cost: ¥500,000)
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| Keywords | Robust optimum design / Surface acoustic wave device / Optimization method / 電子デバイス / 弾性表面波 |
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| Research Abstract |
In recent years, surface acoustic wave (SAW) devices have been used wildly in various mobile and wireless communication systems, such as personal data assistants and mobile phones. The frequency response characteristics of SAW devices are governed primarily by their geometrical structures : the configurations of interdigital transducers (IDTs) and grating reflectors fabricated on piezoelectric substrates. For deciding desirable structures of SAW devices based on the computer simulation, the equivalent circuit model of IDT, which includes several uncertain constant parameters, is usually used. In order to cope well with the designing imperfections caused by the inevitable dispersion of these constant parameters, a robust optimum design technique is proposed. First of all, the robust optimum design of SAW devices is formulated as a constrained optimization problem, in which the robustness of SAW devices is maximized under the constraints of their desirable functions specified by frequency response characteristics. Then, a new penalty function method combined with a variable neighborhood search (VNS) is proposed and applied to the constrained optimization problem. Furthermore, in order to solve the large-sized robust optimum design problem of SAW devices, a genetic local search method combining an evolutionary algorithm with the VNS is also proposed. Computational experiments show that the proposed robust optimum design technique improves the robustness of SAW devices without losing their specified functions.
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Report
(4 results)
Research Products
(19 results)
