Autor: Zhang, Anguo - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Neuro-adaptive cooperative control for high-order nonlinear multi-agent systems with uncertainties
Autorzy:: Peng, Cheng
Zhang, Anguo
Li, Junyu
Tematy:: multiagent system
radial basis function
RBF neural network
sliding mode control
cooperative control
system wieloagentowy
radialna funkcja bazowa
sieć neuronowa RBF
sterowanie ślizgowe; Pokaż więcej
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Powiązania:: https://bibliotekanauki.pl/articles/2055174.pdf Link otwiera się w nowym oknie
Opis:: The consensus problem for a class of high-order nonlinear multi-agent systems (MASs) with external disturbance and system uncertainty is studied. We design an online-update radial basis function (RBF) neural network based distributed adaptive control protocol, where the sliding model control method is also applied to eliminate the influence of the external disturbance and system uncertainty. System consensus is verified by using the Lyapunov stability theorem, and sufficient conditions for cooperative uniform ultimately boundedness (CUUB) are also derived. Two simulation examples demonstrate the effectiveness of the proposed method for both homogeneous and heterogeneous MASs.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Event-triggered cooperative control for high-order nonlinear multi-agent systems with finite-time consensus
Autorzy:: Gong, Shiyin
Zheng, Meirong
Hu, Jing
Zhang, Anguo
Tematy:: multiagent system
cooperative control
event triggered control
neuroadaptive control
prescribed performance
system wieloagentowy
sterowanie wyzwalane zdarzeniami
sterowanie neuroadaptacyjne; Pokaż więcej
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Powiązania:: https://bibliotekanauki.pl/articles/24200691.pdf Link otwiera się w nowym oknie
Opis:: An event-triggered adaptive control algorithm is proposed for cooperative tracking control of high-order nonlinear multiagent systems (MASs) with prescribed performance and full-state constraints. The algorithm combines dynamic surface technology and the backstepping recursive design method, with radial basis function neural networks (RBFNNs) used to approximate the unknown nonlinearity. The barrier Lyapunov function and finite-time stability theory are employed to prove that all agent states are semi-globally uniform and ultimately bounded, with the tracking error converging to a bounded neighborhood of zero in a finite time. Numerical simulations are provided to demonstrate the effectiveness of the proposed control scheme.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Dynamic adjustment neural network-based cooperative control for vehicle platoons with state constraints
Autorzy:: Wang, Ping
Gao, Min
Li, Junyu
Zhang, Anguo
Tematy:: vehicle platoon
dynamic adjustment neural network
DANN
cooperative control
state constraint
konwój pojazdów
sieć neuronowa
ograniczenia stanu; Pokaż więcej
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Powiązania:: https://bibliotekanauki.pl/articles/59123809.pdf Link otwiera się w nowym oknie
Opis:: This paper addresses the challenge of managing state constraints in vehicle platoons, including maintaining safe distances and aligning velocities, which are key factors that contribute to performance degradation in platoon control. Traditional platoon control strategies, which rely on a constant time-headway policy, often lead to deteriorated performance and even instability, primarily during dynamic traffic conditions involving vehicle acceleration and deceleration. The underlying issue is the inadequacy of these methods to adapt to variable time-delays and to accurately modulate the spacing and speed among vehicles. To address these challenges, we propose a dynamic adjustment neural network (DANN) based cooperative control scheme. The proposed strategy employs neural networks to continuously learn and adjust to time varying conditions, thus enabling precise control of each vehicle’s state within the platoon. By integrating a DANN into the platoon control system, we ensure that both velocity and inter-vehicular spacing adapt in response to real-time traffic dynamics. The efficacy of our proposed control approach is validated using both Lyapunov stability theory and numeric simulation, which confirms substantial gains in stability and velocity tracking of the vehicle platoon.
Dostawca treści:: Biblioteka Nauki

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