TY - JOUR
T1 - Dynamic Event-Based Adaptive Fixed-Time Control for Uncertain Strict-Feedback Nonlinear Systems with State Constraints
AU - Shen, Ganghui
AU - Huang, Panfeng
AU - Ma, Zhiqiang
AU - Zhang, Fan
AU - Xia, Yuanqing
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2024
Y1 - 2024
N2 - In this article, the event-triggered fixed-time tracking control is investigated for uncertain strict-feedback nonlinear systems involving state constraints. By employing the universal transformed function (UTF) and coordinate transformation techniques into backstepping design procedure, the proposed control scheme ensures that all states are constrained within the time-varying asymmetric boundaries, and meanwhile, the undesired feasibility condition existing in other constrained controllers can be removed elegantly. Different from the existing static event-triggered mechanism, a dynamic event-triggered mechanism (DETM) is devised via constructing a novel dynamic function, so that the communication burden from the controller to actuator is further alleviated. Furthermore, with the aid of adaptive neural network (NN) technique and generalized first-order filter, together with Lyapunov theory, it is proved that the states of closed-loop system converge to small regions around zero with fixed-time convergence rate. The simulation results confirm the benefits of developed scheme.
AB - In this article, the event-triggered fixed-time tracking control is investigated for uncertain strict-feedback nonlinear systems involving state constraints. By employing the universal transformed function (UTF) and coordinate transformation techniques into backstepping design procedure, the proposed control scheme ensures that all states are constrained within the time-varying asymmetric boundaries, and meanwhile, the undesired feasibility condition existing in other constrained controllers can be removed elegantly. Different from the existing static event-triggered mechanism, a dynamic event-triggered mechanism (DETM) is devised via constructing a novel dynamic function, so that the communication burden from the controller to actuator is further alleviated. Furthermore, with the aid of adaptive neural network (NN) technique and generalized first-order filter, together with Lyapunov theory, it is proved that the states of closed-loop system converge to small regions around zero with fixed-time convergence rate. The simulation results confirm the benefits of developed scheme.
KW - Dynamic event-triggered mechanism (DETM)
KW - fixed-time control
KW - neural networks (NNs)
KW - state constraints
KW - strict-feedback nonlinear systems
UR - http://www.scopus.com/inward/record.url?scp=85166747856&partnerID=8YFLogxK
U2 - 10.1109/TCYB.2023.3293466
DO - 10.1109/TCYB.2023.3293466
M3 - 文章
C2 - 37527309
AN - SCOPUS:85166747856
SN - 2168-2267
VL - 54
SP - 4630
EP - 4642
JO - IEEE Transactions on Cybernetics
JF - IEEE Transactions on Cybernetics
IS - 8
ER -