Preset-Time and Preset-Accuracy Human-in-the-Loop Cluster Consensus Control for MASs Under Stochastic Actuation Attacks
Pei-Ming Liu, Xiang‐Gui Guo, Jianliang Wang, Daniel Coutinho, Zheng‐Guang Wu
Abstract
This article investigates a preset-time and preset-accuracy human-in-the-loop cluster consensus control approach for nonlinear multi-agent systems (MASs) on a directed graph under stochastic actuation attacks. First, a new preset-time and preset-accuracy Zeno-free event-triggered observer that requires neither each agent to access the human agent information nor the first <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$(n-1)$</tex-math></inline-formula> derivatives of the human agent output is designed by using a preset-time and preset-accuracy convergence performance function. Based on this observer, a preset-time and preset-accuracy intrusion-tolerant controller is put forward for every follower agent, wherein the preset-time convergence and steady-state cluster consensus accuracy are assigned a priori. It is worth mentioning that the control strategy is designed in the form of a transformed error, which not only avoids the infinite gain at the preset-time instant but also operates continuously even beyond the preset-time interval. Meanwhile, the preset time and preset accuracy are not affected by the initial conditions, so that the performance function can be preset arbitrarily. To confirm the effectiveness and advantages of the theoretical results, the proposed strategy for cluster consensus control with preset time and preset accuracy is applied to a single link manipulator system.