Adaptive Leader Following in Networks of Discrete-Time Dynamical Systems: Algorithms and Global Convergence Analysis

摘要: Most of the results on adaptive leader following in multiagent systems pertain to continuous-time agent dynamics. It is implicitly presumed that information flow among agents continuous and infinitely fast. Since discrete-time setting, there no need for this assumption, it interest develop methods leader-follower synchronization networks dynamical systems. There main challenges are as follows: 1) general, sample values leader's trajectory arrive at each with different delays; 2) since received samples do not carry imprint a leader, immersed state respective neighbors, have explicit knowledge samples; 3) uncertainty dynamics calls an appropriate rule generating interagent coupling gains. This paper considers unknown linear general order arbitrary trajectory, directed graph topology. Two novel distributed algorithms proposed both cases known control directions. proven all synchronize tracking error $l_2$ sequence, input signals remain bounded, parameter estimates convergent sequences.