Adaptive Tracking Control of Uncertain Nonlinear Multiagent Systems: A Dynamic Event-Based Method via Prescribed-Time Characteristics

The tracking control issue for a class of nonlinear multiagent systems under adaptive fuzzy prescribed-time dynamic event-triggered control is explored in this paper. A DETM relying on the characteristics of prescribed-time functions is designed and characterized by utilizing a prescribed-time mapping function as the triggering threshold. This approach not only mitigates the oscillation issues associated with traditional threshold-based event control inputs, which are often caused by unreasonable thresholds and the demand for enhanced performance, but also significantly reduces the communication burden. Additionally, a conversion strategy for time-varying constraints is considered, allowing users to define the tracking accuracy and settling time regardless of system parameters and initial conditions. It has been proven that the proposed strategy enables the tracking error to converge within a prescribed error range within a specified time frame. The effectiveness and practicality of this scheme are validated through simulation results. Note to Practitioners—The core focus of this work lies in enhancing the effectiveness of engineering applications, with a particular emphasis on optimizing the performance of MASs, efficiently utilizing communication resources, and adapting to uncertainties and external disturbances. These requirements are crucial across various domains, such as circuit systems, unmanned aerial vehicle formations, and sensor network systems. Within the theoretical framework of prescribed-time control, this study integrates prescribed-time characteristics to design a novel DETM. This mechanism not only significantly reduces communication resources but also effectively mitigates potential oscillations in control inputs during critical moments, thereby providing a more robust and efficient solution for practical application scenarios.