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Design Example: Underdamped Parallel RLC Circuit

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Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters

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Surrogate-Assisted Differential Evolution for the Design of Multimode Resonator Topology.

Vladimir Stanovov¹, Sergey Khodenkov¹, Sergey Gorbunov²

¹Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk 660037, Russia.

Sensors (Basel, Switzerland)

|August 10, 2024

Summary

This study introduces an automated method using evolutionary computation and surrogate modeling to optimize multimode resonator designs for microwave devices. The approach efficiently tunes resonator parameters, enhancing performance in communication and radar systems.

Keywords:

Gaussian process amplitude–frequency characteristics differential evolution kriging microwave sensor multimode resonator optimization surrogate-assisted optimization

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Area of Science:

Electromagnetics and Microwave Engineering
Computational Intelligence

Background:

Microstrip devices utilizing multimode resonators are crucial for advanced communication, radar, and navigation systems.
Designing frequency-selective microwave components like bandpass filters is challenging due to computationally intensive electrodynamic modeling.
Identifying novel microstrip resonator topologies with superior frequency-selective properties is a key research area.

Purpose of the Study:

To develop an automated method for optimizing the conductor topology parameters of multimode resonators.
To enhance the efficiency of designing wideband bandpass filters, diplexers, and multiplexers.
To present a general approach for formulating target functions in resonator optimization.

Main Methods:

Employs a combination of evolutionary computation, specifically a variant of the differential evolution optimizer, and surrogate modeling.
Utilizes Gaussian processes to build a model of the target function landscape for efficient solution searching.
Applies a general target function formulation approach within the optimization framework.

Main Results:

Successfully demonstrated the algorithm's capability in tuning three-mode and six-mode resonators to specified parameters for microwave filters.
The surrogate-assisted evolutionary algorithm significantly improved the overall performance in optimizing resonator topologies.
Validated the effectiveness of the automated search approach for complex electromagnetic device design.

Conclusions:

The proposed automated search method effectively optimizes multimode resonator parameters, overcoming the limitations of traditional modeling.
Surrogate-assisted evolutionary computation offers a significant performance improvement for designing advanced microwave components.
This approach facilitates the discovery of high-quality resonator structures with unique frequency-selective properties for practical applications.