Event-Triggered Adaptive Neural Control for Fractional-Order Nonlinear Systems Based on Finite-Time Scheme
针对分数阶非线性系统，提出一种基于反步法的事件触发自适应神经控制方案，利用分数阶Lyapunov函数理论保证跟踪误差在有限时间内收敛到原点附近的小区域，并通过仿真验证了有效性。
This article addresses the finite-time event-triggered adaptive neural control for fractional-order nonlinear systems. Based on the backstepping technique, a novel adaptive event-triggered control scheme is proposed, and finite-time stability criteria are introduced with the aim to ensure that the tracking error enters into a small region around the origin in finite time. Finally, the stability of the closed-loop system is ensured via a fractional Lyapunov function theory and two simulation examples were used to prove the validity of the designed control scheme.