Sep 2026· IEEE Systems Journal· Vol 20, pp. 1094-1105· 0 citations· 55 references
Abstract
Most existing results on nonlinear systems with unknown control directions (CDs) focus on asymptotic tracking. This article investigates the problem of adaptive predefined-time (PT) precise tracking for a class of nonlinear multiagent systems (MASs) with unknown finitely switching CDs and time-varying input delay. A novel control framework is established by introducing monotonically increasing sequences, which extends the classical Nussbaum function methodology to scenarios involving finitely switchable and completely unknown CDs via a proof by contradiction mechanism. Moreover, to compensate for the input delay, a class of delay compensation signals is introduced. By incorporating fuzzy logic systems and bounded estimation techniques, it is rigorously proven that the tracking error converges to zero within a PT, while simultaneously ensuring that full-state constraints are satisfied and all closed-loop signals are semiglobally ultimately bounded. The proposed method offers improved control performance and a broader applicability compared to existing approaches. Numerical simulations are provided to demonstrate the effectiveness of the proposed strategy.
This paper investigates the event-triggered optimal hybrid control problem for switched nonlinear multiagent systems (SNMASs) with unknown dynamics and external disturbances, where both the optimal consensus control policy and the optimal switching policy are designed. By casting the control problem as a switched multi...
Qiancheng Wang, Zheng-Rong Xiang· ISA transactions· 0 citations
This paper studies the prescribed-time tracking control problem with output constraints for stochastic nonlinear systems over an infinite horizon, motivated by ship maneuvering dynamics. The steady-state tracking accuracy of existing methods is uncertain due to unknown system parameters, which may fail to meet high-pre...
Yi-Xuan Yuan, Li-Ping Xie, Jun-Sheng Zhao et al.· ISA transactions· 0 citations
In this paper, a novel phase-error-based Q-learning algorithm is proposed to solve the optimal tracking control problems for unknown discrete-time nonlinear systems. For the first time, phase errors between the system state and the desired trajectory are incorporated into the performance index, which rigorously guarant...
Bo-Yu Wen, Xin Chen, Wojciech Paszke et al.· International Journal of Con...· 0 citations
This paper investigates the predefined-time adaptive neural tracking control problem for a class of nonlinear pure feedback systems with full state constraints. A novel barrier Lyapunov function (BLF) integrated with a predefined-time performance function (PTPF) is constructed to ensure that the tracking error converge...
Yang Li, Ya-Qi Yu, Quan-Min Zhu et al.· Mathematics· 0 citations
Through rigorous mathematical analysis and numerical simulations, it can be concluded that the proposed control scheme can not only drive all system variables to converge to steady states within a prescribed time in probability, but also make the output track the desired signal without violating the output constraint.
Daohong Zhu, Lian-Di Fang, Hong-Yi Xia· Measurement and control (Lon...· 0 citations
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