p th moment consensus of multi‐agent systems with relative state‐dependent measurement noises and time delays

Mean‐square output consensus of heterogeneous multi‐agent systems with communication noises

“…Remark Comparison of ref. [28], we just considers the competition between each other (), so the mean‐square consensus of the systems is easier to achieve, where here. At the same time, from the perspective of state transition matrix, reference [29] can finally realise the mean‐square consensus of compensator.…”

“…By introducing compensator, the controller can achieve stability better than the general control. Thirdly, the results obtained in this paper can be simplified to the results of the above work in some special cases, such as first-order, second-order or high-order homogeneous MAS [21][22][23][24] with communication noises, and mixed MAS [27][28][29] with noises.…”

“…[23][24][25], under the influence of communication noises, the author separately takes uncertain factors such as Markov switching topology [23] and time-delays [24,25] into consideration, and studies the consensus in the sense of mean-square. In addition, some corresponding results are given for the interference of the leader-following systems and the high-order homogeneous MASs under the communication noises [26][27][28][29].…”

“…As mentioned above, the dynamic trajectories among the agents are not always the same, so it is of practical significance to design appropriate control strategies to reduce the interference of communication noises, so as to realise the problem of meansquare output consensus of heterogeneous MAS. As far as we know, however, this issue has been less discussed, and this problem cannot be solved directly by the methods [27][28][29]. Based on the above discussion, we are deeply inspired.…”

Non‐fragile robust exponential stabilisation and control for uncertain stochastic systems with non‐linearity and mixed delays

“…Meanwhile, based on Itô‐type stochastic differential equations, many issues have been discussed, see e.g. iterative learning control [6], filtering problem [7] and consensus control [8]. Time‐delay exists widely in practice and affects the system performance, which often occurs in state [9], control input [10] or measurement output [11].…”