A Dropout Compensation ILC Method for Formation Tracking of Heterogeneous Multi-Agent Systems with Loss of Multiple Communication Packets

Abstract

<jats:p>In this paper, the formation tracking problem for heterogeneous multi-agent systems with loss of multiple communication packets is considered using the iterative learning control (ILC) method. A dropout compensation ILC method is presented to construct effective distributed iterative learning protocols. The convergence conditions are given based on the frequency-domain analysis by using the general Nyquist stability criterion and Greshgorin’s disk theorem. The results show that the multi-agent system with different packet loss rate can achieve formation tracking without reducing the convergence speed. Numerical simulation results show the effectiveness of the proposed dropout compensation ILC method.</jats:p>

The Weighted Group Consensus for a Kind of Discrete Heterogeneous Multi-Agent Systems With Time Delay and Packet Loss in Cooperative-Competitive Networks Based on Self-Adaptive Controller

“…Packet loss is one of the main factors of system stability. Therefore, it is very necessary for us to investigate the group consensus of MASs with packet loss [30][31][32]. In [30], formation tracking for heterogeneous multi-agent systems with loss of multiple communication packets is investigated using the iterative learning control (ILC) method.…”

“…Therefore, it is very necessary for us to investigate the group consensus of MASs with packet loss [30][31][32]. In [30], formation tracking for heterogeneous multi-agent systems with loss of multiple communication packets is investigated using the iterative learning control (ILC) method. Convergence conditions are given based on frequencydomain analysis using the general Nyquist stability criterion and Greshgorin's disk theorem.…”