PMID- 37339030
OWN - NLM
STAT- Publisher
LR  - 20240215
IS  - 2162-2388 (Electronic)
IS  - 2162-237X (Linking)
VI  - PP
DP  - 2023 Jun 20
TI  - Observer-Based Fault-Tolerant Finite-Time Control of Nonlinear Multiagent 
      Systems.
LID - 10.1109/TNNLS.2023.3279890 [doi]
AB  - In this article, an adaptive neural containment control for a class of nonlinear 
      multiagent systems considering actuator faults is introduced. By using the 
      general approximation property of neural networks, a neuro-adaptive observer is 
      designed to estimate unmeasured states. In addition, in order to reduce the 
      computational burden, a novel event-triggered control law is designed. 
      Furthermore, the finite-time performance function is presented to improve the 
      transient and steady-state performance of the synchronization error. Utilizing 
      the Lyapunov stability theory, it will be shown that the closed-loop system is 
      cooperatively semiglobally uniformly ultimately bounded (CSGUUB), and the 
      followers' outputs reach the convex hull constructed by the leaders. Moreover, it 
      is shown that the containment errors are limited to the prescribed level in a 
      finite time. Eventually, a simulation example is presented to corroborate the 
      capability of the proposed scheme.
FAU - Salmanpour, Yasaman
AU  - Salmanpour Y
FAU - Arefi, Mohammad Mehdi
AU  - Arefi MM
FAU - Khayatian, Alireza
AU  - Khayatian A
FAU - Yin, Shen
AU  - Yin S
LA  - eng
PT  - Journal Article
DEP - 20230620
PL  - United States
TA  - IEEE Trans Neural Netw Learn Syst
JT  - IEEE transactions on neural networks and learning systems
JID - 101616214
SB  - IM
EDAT- 2023/06/20 19:14
MHDA- 2023/06/20 19:14
CRDT- 2023/06/20 12:33
PHST- 2023/06/20 19:14 [pubmed]
PHST- 2023/06/20 19:14 [medline]
PHST- 2023/06/20 12:33 [entrez]
AID - 10.1109/TNNLS.2023.3279890 [doi]
PST - aheadofprint
SO  - IEEE Trans Neural Netw Learn Syst. 2023 Jun 20;PP. doi: 
      10.1109/TNNLS.2023.3279890.