Gain‐scheduled robust control for multi‐agent linear parameter‐varying systems with communication delays

Abstract

This study deals with the problem of gain-scheduled robust control for multi-agent linear parameter varying (LPV) systems with or without communication delays. The system matrices are assumed to depend on the scheduling parameters, which are supposed to be time-varying within a priori known bounds. First, a linear transformation matrix is constructed from the directed spanning tree of the communication topology of the agents, which equivalently transforms the robust consensus control problem of multi-agent LPV systems into the robust stability problem of a set of parameter-dependent systems. What's more, the effect of the time-varying communication delays is considered, and consensus condition in terms of linear matrix inequalities (LMIs) is derived by using the parameter-dependent Lyapunov-Krasovskii approach. Then, the control gain matrices are obtained through solving a convex optimization problem. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.

Fault-tolerant formation consensus control for time-varying multi-agent systems with stochastic communication protocol

“…Compared with time-invariant MASs, the convergence analysis on the FTC problem for time-varying MASs is more challenging due to the complexity caused by time variance [27]. Consensus problem is a fundamental problem in cooperative control of MASs, to mention a few, the leader-following consensus for time-varying MASs has been adequately discussed in [27][28][29][30][31][32]. Besides, in [33][34][35][36], many distributed algorithms have been developed for consensus problems of nonlinear time-varying MASs models expressed via various representations.…”

Aperiodic sampled‐data consensus control for homogeneous and heterogeneous multi‐agent systems: A looped‐functional method

“…[12][13][14] Therefore, many more studies have become available on consensus control for MASs with time delays. 15,16 Moreover, to reduce the cost of communication, energy and computation, it is also necessary to further consider the problem that agents cannot communicate continuously in networked environments with limited resources. 17 Hence, a nonuniform sampling pattern is usually used.…”

“…However, it is worth noting that time delays commonly exist in practical systems, which cause a series of effects on the dynamic behavior of the agents 12‐14 . Therefore, many more studies have become available on consensus control for MASs with time delays 15,16 . Moreover, to reduce the cost of communication, energy and computation, it is also necessary to further consider the problem that agents cannot communicate continuously in networked environments with limited resources 17 .…”