Hybrid spiral-dynamic bacteria-chemotaxis algorithm with application to control two-wheeled machines


This paper presents the implementation of the hybrid spiral-dynamic bacteria-chemotaxis (HSDBC) approach to control two different configurations of a two-wheeled vehicle. The HSDBC is a combination of bacterial chemotaxis used in bacterial forging algorithm (BFA) and the spiral-dynamic algorithm (SDA). BFA provides a good exploration strategy due to the chemotaxis approach. However, it endures an oscillation problem near the end of the search process when using a large step size. Conversely; for a small step size, it affords better exploitation and accuracy with slower convergence. SDA provides better stability when approaching an optimum point and has faster convergence speed. This may cause the search agents to get trapped into local optima which results in low accurate solution. HSDBC exploits the chemotactic strategy of BFA and fitness accuracy and convergence speed of SDA so as to overcome the problems associated with both the SDA and BFA algorithms alone. The HSDBC thus developed is evaluated in optimizing the performance and energy consumption of two highly nonlinear platforms, namely single and double inverted pendulum-like vehicles with an extended rod. Comparative results with BFA and SDA show that the proposed algorithm is able to result in better performance of the highly nonlinear systems.

Publication DOI: https://doi.org/10.1186/s40638-017-0059-1
Divisions: College of Health & Life Sciences
College of Health & Life Sciences > Cell & Tissue Biomedical Research
Additional Information: © The Author(s) 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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Related URLs: https://jrobio. ... 0638-017-0059-1 (Publisher URL)
PURE Output Type: Article
Published Date: 2017-06-16
Accepted Date: 2017-05-05
Authors: Goher, K M
Almeshal, A M
Agouri, S A
Nasir, A N K
Tokhi, M O
Alenezi, M R
Al Zanki, T
Fadlallah, S O



Version: Published Version

License: Creative Commons Attribution

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