A New MIMO ANFIS-PSO Based NARMA-L2 Controller for Nonlinear Dynamic Systems
- Submitting institution
-
Brunel University London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 176-176721-9425
- Type
- D - Journal article
- DOI
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10.1016/j.engappai.2017.04.016
- Title of journal
- Engineering Applications Of Artificial Intelligence
- Article number
- -
- First page
- 265
- Volume
- 62
- Issue
- -
- ISSN
- 0952-1976
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2017
- URL
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https://www.sciencedirect.com/science/article/pii/S0952197617300805/pdfft?md5=098cb383a8cba792ab3e2e3db0cc80fc&pid=1-s2.0-S0952197617300805-main.pdf
- 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)
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4 - Sensors & Digital Systems
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- In this paper a multi-input / multi-output intelligent control system is designed to control a complex multi-variable distillation column plant. The plant is highly non-linear and very difficult to control using conventional PID controllers. The designed controller is based on non-linear auto-regressive model which incorporates a neuro-fuzzy system to model the process behaviour. The achieved result are superior to conventional PID control system.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -