Indirect Adaptive Neural Control based on VLRs of nonlinear MIMO systems

Hamza, Rabab; Yassin, Farhat; Zribi, Akram

doi:10.1109/sta56120.2022.10019008

Search citation statements

Order By: Relevance

Paper Sections

Select...

An Ne1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The activation of emulator neurons evolves according to equation (1) (Farhat et al, 2021; Rabab et al, 2022)…”

Section: An Nementioning

confidence: 99%

A novel neural emulator identification of nonlinear dynamical systems using Lyapunov stability theory

Hamza,

Zribi,

Farhat

2023

Transactions of the Institute of Measurement and Control

View full text Add to dashboard Cite

This paper deals with a new weight-updating algorithm using Lyapunov stability theory (LST) for the training of a neural emulator (NE), of nonlinear systems, connected by an autonomous algorithm inspired from the real-time recurrent learning (RTRL). The proposed method is formulated by an inequality-constraint optimization problem where the Lagrange multiplier theory is used as the optimization tool. The contribution of this paper is the integration of the LST into the Lagrange constraint function to synthesize a new analytical adaptation gain rate satisfying the asymptotic stability of the NE and providing good emulation performances. To confirm the good performances and the convergence ability of the proposed adaptation algorithm, a numerical example and an experimental validation on a chemical reactor are proposed.

show abstract

“…The activation of emulator neurons evolves according to equation (1) (Farhat et al, 2021; Rabab et al, 2022)…”

Section: An Nementioning

confidence: 99%