“Compressor Surge Control Using Lyapunov Neural Networks”

Authors: Åse Neverlien, Signe Moe and Jan T. Gravdahl,
Affiliation: NTNU, Department of Engineering Cybernetics and SINTEF
Reference: 2020, Vol 41, No 2, pp. 41-49.

Keywords: Nonlinear process control, Industrial applications of process control

Abstract: In this paper surge control in a compression system using a close-coupled valve (CCV) is proposed. The control design is based on Lyapunov control theory in combination with neural networks (NNs) and focuses on minimization of loss of energy in the compressor system. The approach allows for control design with guaranteed region of attraction when considering saturated controls. The CCV modifies the characteristics of the compressor and thus stabilizes the equilibrium beyond the original surge line at the expense of a pressure drop over the valve. Two control laws for the compression system are proposed. The first control law provides a global asymptotically stable equilibrium. The second control law focuses on minimization of the pressure drop over the valve, and local asymptotically stability is proven.

PDF PDF (2778 Kb)        DOI: 10.4173/mic.2020.2.1

References:
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BibTeX:
@article{MIC-2020-2-1,
  title={{Compressor Surge Control Using Lyapunov Neural Networks}},
  author={Neverlien, Åse and Moe, Signe and Gravdahl, Jan T.},
  journal={Modeling, Identification and Control},
  volume={41},
  number={2},
  pages={41--49},
  year={2020},
  doi={10.4173/mic.2020.2.1},
  publisher={Norwegian Society of Automatic Control}
};