Guaranteed-Cost Consensus Control for High-Dimensional Multi-Agent Systems With Input Delays and Parameter Uncertainties

In this paper, the problem of consensus control is investigated for a kind of multi-agent systems (MAS) in high-dimensional form. Both the nonlinear dynamics and norm-bound uncertainties are taken into account, which makes the model more comprehensive than those in existing literature. By employing the related error (between each agent and its neighbors) and considering the time-varying input delay, the consensus protocol is constructed to force agents to close to the consensus dynamical function. An augmented closed-loop system is established by taking use of properties of Laplacian matrix and the state space decomposition method. A few of sufficient criteria are gained with the help of feasible solutions for linear matrix inequalities. The asymptotical stability of error system is realized and the upper-bound is obtained for the cost function consisting of both the consensus regulation performance and the control energy consumption. An illustrative example and the corresponding simulations are given for verifying the validity of our results.