Multi-objective evolutionary design of robust controllers on the grid
- Submitting institution
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Sheffield Hallam University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1396
- Type
- D - Journal article
- DOI
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10.1016/j.engappai.2013.09.015
- Title of journal
- Engineering Applications of Artificial Intelligence
- Article number
- -
- First page
- 17
- Volume
- 27
- Issue
- -
- ISSN
- 0952-1976
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2014
- 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
-
1
- Research group(s)
-
-
- Citation count
- 8
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Originality: A novel HPC-based framework is proposed that allows for using evolutionary multi-objective optimisation to solve computationally expensive problems relying on model-based design and simulation routines.
Significance: Building on work originally funded by EPSRC (under the DAME project (GR/R67668/01)) and Innovate UK (with Rolls-Royce PLC under the BROADEN project (project reference 100662)), the proposed framework is used to optimise a lateral stability controller for a real-world aircraft using modern multi-objective evolutionary model-based control system design techniques. The HPC-based EMOO framework has been deployed on Rolls-Royce’s internal computing grid.
Rigour: Results are analysed for statistical significance using multiple quality metrics.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -