Event-triggered consensus control of continuous-time stochastic multi-agent systems

Periodically intermittent control for stochastic nonlinear delay systems with dynamic event‐triggered mechanism

“…It's easy to find that under this control scheme, each agent updates only at its own event-triggered. [46][47][48] Denote…”

“…Combining the information of neighbor agent, the distributed control protocol is constructed as follows: $$$$ {u}_i(t)=k\sum \limits_{j\in N}{a}_{ij}\left({x}_j\left({t}_{k,j}\right)-{x}_i\left({t}_{k,i}\right)\right),t\in \left[{t}_{k,i},{t}_{k,i+1}\right), $$$$ where $$$ k $$$ is the control gain. It's easy to find that under this control scheme, each agent updates only at its own event‐triggered 46‐48 . Denote $$$ {p}_i(t)={\sum}_{j\in N}{a}_{ij}\left({x}_i\left({t}_{k,i}\right)-{x}_j\left({t}_{k,j}\right)\right) $$$, the measurement error denotes as $$$ {e}_i(t)={x}_i\left({t}_{k,i}\right)-{x}_i(t) $$$.…”

Robust consensus of multi‐agent systems with multiplicative uncertainties and its application in time synchronization

“…[5][6][7] However, in practice, various uncertainties in the information collection and transmission processes may bring uncertainties into models of consensus problems, such as the measurement and communication noise. 8,9 Recently, the study of the consensus problem of MASs with non-precise information is receiving much attention from researchers. [10][11][12][13] Depending on the existing form of the uncertainty in the system model, consensus problems of MASs can be classified into the problem with additive uncertainties and the problem with multiplicative uncertainties.…”

“…Especially, under the precise information collection and transmission assumption, many consensus results have been obtained 5‐7 . However, in practice, various uncertainties in the information collection and transmission processes may bring uncertainties into models of consensus problems, such as the measurement and communication noise 8,9 . Recently, the study of the consensus problem of MASs with non‐precise information is receiving much attention from researchers 10‐13 …”

Adaptive Fuzzy Command Filtered Finite-Time Tracking Control for Uncertain Nonlinear Multi-Agent Systems with Unknown Input Saturation and Unknown Control Directions

“…The consensus problem for multi-agent systems has been widely investigated over the past few decades due to its applications in aircraft formation control [1], autonomous unmanned systems [2], wireless sensor networks [3], and other fields. Many remarkable research findings, such as the adaptive cooperative control of nonlinear multi-agent systems [4], adaptive distributed control of non-affine multi-agent systems [5], iterative learning control of nonlinear multi-agent systems [6], distributed optimization control of linear multi-agent systems [7,8], adaptive event-triggered control of multi-agent systems [9,10], and so on, have been extensively reported. It is not difficult to find that in many existing achievements on multi-agent systems, the fuzzy logic system and neural network approach have been successfully applied to approximate the unknown nonlinear dynamics by many researchers; see [11][12][13][14] and references therein.…”