Shen Ganghui, Huang Panfeng, Ma Zhiqiang, Zhang Fan, Xia Yuanqing
IEEE Trans Cybern. 2024 Aug;54(8):4630-4642. doi: 10.1109/TCYB.2023.3293466. Epub 2024 Jul 18.
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.
本文针对具有状态约束的不确定严格反馈非线性系统，研究了事件触发固定时间跟踪控制问题。通过将通用变换函数（UTF）和坐标变换技术应用于反步设计过程，所提出的控制方案确保所有状态都被约束在时变非对称边界内，同时，可以巧妙地消除其他约束控制器中存在的不理想的可行性条件。与现有的静态事件触发机制不同，通过构造一个新颖的动态函数设计了一种动态事件触发机制（DETM），从而进一步减轻了从控制器到执行器的通信负担。此外，借助自适应神经网络（NN）技术和广义一阶滤波器，结合李雅普诺夫理论，证明了闭环系统的状态以固定时间收敛速率收敛到零附近的小区域。仿真结果证实了所提出方案的有效性。
