Event-based distributed adaptive fuzzy average tracking of high-order integrator multi-agent nonlinear systems
Gongdi Fu, Ming Zhu, Shuai Liu, Haotian Xu · International Journal of Systems Science · 2025
This paper investigates the event-triggered distributed average tracking (ETDAT) of an nth order multi-agent system (MAS) with unknown nonlinear functions and disturbances. An observer is designed to estimate the unmeasurable states of the system in which the unknown nonlinearities and disturbances are approximated using fuzzy logic and an adaptive control method (ACM), respectively. A control protocol is then developed to ensure the MAS tracks its reference system, in which the process includes estimation errors tending to zero and the states of the observers tracking the reference system. The reference system and its control protocol are designed to track the average of the target system. As a result, the MAS firstly tracks the reference system and subsequently tracks the target system. An event-triggered controller is proposed for the reference system, and Lyapunov functions are employed to prove the convergence of the algorithm. Meanwhile, Zeno behaviour is excluded in the whole process. The effectiveness of the proposed approach is demonstrated through numerical simulations.