  It poses technical difficulty to achieve stable tracking even for single
mismatched nonlinear strict-feedback systems when intermittent state feedback
is utilized. The underlying problem becomes even more complicated if such
systems are networked with directed communication and state-triggering setting.
In this work, we present a fully distributed neuroadaptive tracking control
scheme for multiple agent systems in strict-feedback form using triggered state
from the agent itself and the triggered states from the neighbor agents. To
circumvent the non-differentiability of virtual controllers stemming from
state-triggering, we first develop a distributed continuous control scheme
under regular state feedback, upon which we construct the distributed
event-triggered control scheme by replacing the states in the preceding scheme
with the triggered ones. Several useful lemmas are introduced to allow the
stability condition to be established with such replacement, ensuring that all
the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB),
with the output tracking error converging to a residual set around zero.
Besides, with proper choices of the design parameters, the tracking performance
in the mean square sense can be improved. Numerical simulation verifies the
benefits and efficiency of the proposed method.
