Data‐Driven Adaptive Event‐Triggered Terminal Sliding Mode Control for Nonlinear Systems With Prescribed Performance

ABSTRACT Tracking control for nonlinear systems considering unknown disturbances and tracking‐error constraint. Firstly, a dynamic linearized model is presented and, to decrease the computational burden, the pseudo‐partial derivatives and the unknown disturbance are estimated based on an event‐triggered mechanism. Secondly, an output observer is proposed due to the event‐triggered scheme and the boundedness of the output estimation error is ensured using Lyapunov theory. The proposed event‐triggered condition is designed based on the dead‐zone operator to avoid the Zeno phenomenon during the process. The novelty of this work lies in integrating prescribed performance functions with adaptive terminal sliding mode control under a novel event‐triggered design, which simultaneously guarantees finite‐time bounded tracking, reduces chattering, and avoids unnecessary updates. More precisely, according to the Lyapunov theory and the proposed control law, it is guaranteed that the trajectories of the terminal sliding surface stay in a bounded region in finite time. Compared with existing event‐triggered or data‐driven SMC approaches, the proposed framework eliminates the need for complex disturbance estimators, achieves robustness without precise model information, and enhances computational efficiency. Finally, two numerical simulations and one experimental implementation using the Speedgoat Baseline device are considered to verify the efficacy and superiority of the proposed control method.