Asymptotic bounded consensus tracking of double-integrator multi-agent systems with a bounded-jerk target via sampled-data control

This study investigates the asymptotic bounded consensus tracking problems of double-integrator multi-agent systems (MASs) with an asymptotically-unbounded-acceleration and bounded-jerk target via sampled-data control. An improved sampled-data consensus tracking protocol is proposed to guarantee that double-integrator MASs track an asymptotically-unbounded-acceleration and bounded-jerk target available to only a portion of agents. The augmented matrix method and the eigenvalue analysis method are employed for deriving the necessary and sufficient conditions given in the form of the allowable scope of the sampling period. The existence of the non-empty allowable scope of the sampling period theoretically shows the effectiveness of the proposed protocol and comparison simulations numerically illustrate the effectiveness of the proposed protocol.