Biologically inspired rate control of chaos
- Submitting institution
-
Oxford Brookes University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 185739574
- Type
- D - Journal article
- DOI
-
10.1063/1.5008892
- Title of journal
- Chaos
- Article number
- 103122
- First page
- -
- Volume
- 27
- Issue
- 10
- ISSN
- 1054-1500
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
0
- Research group(s)
-
-
- Citation count
- 2
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This highly innovative approach to control of complex systems is derived from the enzymatic
control in biosystems. The method allows the control of complex interacting systems, such as
spatiotemporal chaotic systems, and is based on only local dynamics. This method has extensive
applications to understand complex biological dynamic behaviour, allows control of physical
nonlinear systems, such as combustion engines, wind turbines, and bioreactors to improve
performance, efficiency and stability and it is the basis of a patent (WO2013064840A1). The
method has sparked increased interest in control aspects of biosystems, and has led directly to
novel methods for machine learning.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -