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Conference papers
A Novel Tuning Approach for MPC Parameters Based on Artificial Neural Network: An application to FOPDT System
Abstract : A successful implementation of Model Predictive Control (MPC) requires appropriately tuned parameters. In this paper an Artificial-Neural-Network (ANN) based approach is presented and detailed in the case of a First Order Plus Dead Time (FOPDT) control-lable system. The original part of our approach lies in its capability to tune the MPC parameters using Particle-Swarm-Optimization (PSO) and Online-Sequential-Extreme-Learning-Machine(OS-ELM). This approach allows also to reach efficiently closed-loop stability. The effectiveness of our approach has been emphasized by comparing the obtained performances to other existing methods.
Cited literature [18 references]
https://hal-normandie-univ.archives-ouvertes.fr/hal-02407974
Contributor : Nicolas Langlois <>
Submitted on : Thursday, December 12, 2019 - 5:02:55 PM
Last modification on : Monday, September 7, 2020 - 4:30:03 PM
Long-term archiving on: : Friday, March 13, 2020 - 11:02:17 PM
Contributor : Nicolas Langlois <>
Submitted on : Thursday, December 12, 2019 - 5:02:55 PM
Last modification on : Monday, September 7, 2020 - 4:30:03 PM
Long-term archiving on: : Friday, March 13, 2020 - 11:02:17 PM
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Article_ACD_corrigé.pdf
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