Synergy of ( $${\text{H}}_{2}$$ H 2, $${\text{H}}_{\infty }$$ H ∞ ) norms for nonlinear optimal PEMFC dynamic MIMO model reduction using a novel EAO approach

Zohra Touati, Slami Saadi (), Mecheri Kious and Khaled Omer Mokhtar Touati
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Zohra Touati: Ammar Thelidji University of Laghouat
Slami Saadi: Ziane Achour University of Djelfa
Mecheri Kious: Ammar Thelidji University of Laghouat
Khaled Omer Mokhtar Touati: Ziane Achour University of Djelfa

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 3, No 28, 1396-1409

Abstract: Abstract In this paper, a new nature-inspired Artificial Ecosystem Optimization (AEO) methodology is presented for reducing the complexity of nonlinear PEMFC SR-12 500 W system. From the point view of this system, the hydrogen and oxygen pressures $$P_{H2} = 60\,{\text{atm}}$$ P H 2 = 60 atm , $$P_{O2} = 30 \,{\text{atm}}$$ P O 2 = 30 atm as two inputs, the cell voltage and current as two outputs.By implementation of identification technique, the state space model of PEMFC stack is generated using nlarx modelling procedures where the obtained model is reduced their order by AEO method. The AEO mimics the energy flow behaviour between living organisms in a natural ecosystem, including production, consumption, and decomposition.This algorithm minimize the synergy ( $${\text{H}}_{2} ,{\text{H}}_{\infty }$$ H 2 , H ∞ ) norm of error between full PEMFC model and reduced order model. The obtained results are compared with the other optimization algorithms such as MRFO,SSA,ALO and GWO, and they are confirmed that the approximate model obtained by proposed algorithm has faster convergence and better approximation performance in synergy ( $${\text{H}}_{2} ,{\text{H}}_{\infty }$$ H 2 , H ∞ ) norm than those obtained by comparative algorithms in addition, it is proven to be accurate and reliable to investigate the PEMFC optimum global reduced order model which preserved the main behaviour of original PEMFC SR-12 500 W model.

Keywords: ( $${\text{H}}_{2}; {\text{H}}_{\infty }$$ H 2; H ∞ ) norms; Synergy; Nlarx; PEMFC500W; Model order reduction; AEO algorithm (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s13198-021-01485-1

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