Next Article in Journal
Spectrum Allocation Based on an Improved Gravitational Search Algorithm
Previous Article in Journal
Special Issue on Computational Intelligence and Nature-Inspired Algorithms for Real-World Data Analytics and Pattern Recognition
Article Menu

Export Article

Open AccessArticle
Algorithms 2018, 11(3), 26; https://doi.org/10.3390/a11030026

A Novel Evolutionary Algorithm for Designing Robust Analog Filters

1,2
,
1,2
and
2,3,*
1
Key Laboratory of Advanced Manufacturing Technology of Ministry of Education, Guizhou University, Guiyang 550025, China
2
School of Mechanical Engineering, Guizhou University, Guiyang 550025, China
3
Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA
*
Author to whom correspondence should be addressed.
Received: 12 November 2017 / Revised: 24 February 2018 / Accepted: 27 February 2018 / Published: 1 March 2018
View Full-Text   |   Download PDF [674 KB, uploaded 2 March 2018]   |  

Abstract

Designing robust circuits that withstand environmental perturbation and device degradation is critical for many applications. Traditional robust circuit design is mainly done by tuning parameters to improve system robustness. However, the topological structure of a system may set a limit on the robustness achievable through parameter tuning. This paper proposes a new evolutionary algorithm for robust design that exploits the open-ended topological search capability of genetic programming (GP) coupled with bond graph modeling. We applied our GP-based robust design (GPRD) algorithm to evolve robust lowpass and highpass analog filters. Compared with a traditional robust design approach based on a state-of-the-art real-parameter genetic algorithm (GA), our GPRD algorithm with a fitness criterion rewarding robustness, with respect to parameter perturbations, can evolve more robust filters than what was achieved through parameter tuning alone. We also find that inappropriate GA tuning may mislead the search process and that multiple-simulation and perturbed fitness evaluation methods for evolving robustness have complementary behaviors with no absolute advantage of one over the other. View Full-Text
Keywords: robust design; evolutionary algorithms; computational synthesis; genetic programming; bond graphs; analog filters; automated design robust design; evolutionary algorithms; computational synthesis; genetic programming; bond graphs; analog filters; automated design
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Li, S.; Zou, W.; Hu, J. A Novel Evolutionary Algorithm for Designing Robust Analog Filters. Algorithms 2018, 11, 26.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Algorithms EISSN 1999-4893 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top