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Output-mask-based adaptive NN control for stochastic time-delayed multi-agent systems with a unified event-triggered approach.
- Source :
-
Applied Mathematics & Computation . Aug2024, Vol. 475, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
-
Abstract
- This paper investigates a class of output-mask-based adaptive neural network (NN) tracking control for nonlinear stochastic time-delayed multi-agent systems (STMASs) based on a unified event-triggered approach. The output signal relies on an output mapping acted as a mask, defined as a privacy-protection-like method, so that the internal state of one agent cannot be identified by other distrustful eavesdroppers or attackers. Moreover, the construction of a unified event-triggered control scheme retains the advantages of the saturation threshold triggering strategy, incorporates distributed errors, and increases the flexibility of thresholds. Furthermore, for stochastic time-delay multi-agent systems, the initial value limitation of the conventional first-order filter is removed by a first-order Levant differentiator, and a new estimation term in the fuzzy observer is established to solve the nonlinear fault. The unknown function in pure-feedback form is addressed via combining Butterworth low-pass filter and radial basis function neural networks (RBF NNs). Finally, the boundedness of all signals in the closed-loop systems is demonstrated, and the effectiveness of the proposed algorithm is verified by some simulation results. • This paper proposes a privacy-protection-like scheme for continuous systems to make those signals transmitted in ciphertext. • A unified approach for event-triggered control, namely dynamic saturation threshold event trigger, was established. • The proposed method relaxes two conditions and reduces the conservatism. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00963003
- Volume :
- 475
- Database :
- Academic Search Index
- Journal :
- Applied Mathematics & Computation
- Publication Type :
- Academic Journal
- Accession number :
- 177146953
- Full Text :
- https://doi.org/10.1016/j.amc.2024.128725