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Tracking Consensus of Networked Random Nonlinear Multi-agent Systems with Intermittent Communications

Ali Azarbahram

TL;DR

This work addresses tracking consensus for networks of $N$ followers with high-order nonlinear strict-feedback MASs in the presence of colored disturbances modeled as a wide stationary process $\xi(t)$. It introduces a linear auxiliary trajectory and an intermittent communication scheme with distributed virtual systems, and provides a Lyapunov-based analysis showing the closed-loop system is noise-to-state practically stable in probability (NSpS-P) and that agents track the leader within a bounded error. The design employs a stabilizable pair $(\bm{A},\bm{B})$ and a gain $\bm{K}=c_0\bm{B}^T\bm{P}$, along with neural-network based function approximation to handle unknown nonlinearities, and establishes resilience bounds on OFF-mode durations that guarantee eventual tracking consensus within $\varepsilon^{[e]}$. Simulation on a network of four agents demonstrates robust tracking under intermittent links and colored noise, highlighting the practical impact for resilient networked control systems.

Abstract

The paper proposes an intermittent communication mechanism for the tracking consensus of high-order nonlinear multi-agent systems (MASs) surrounded by random disturbances. Each collaborating agent is described by a class of high-order nonlinear uncertain strict-feedback dynamics which is disturbed by a wide stationary process representing the external noise. The resiliency level of this networked control system (NCS) to the failures of physical devices or unreliability of communication channels is analyzed by introducing a linear auxiliary trajectory of the system. More precisely, the unreliability of communication channels sometimes makes an agent incapable of sensing the local information or receiving it from neighboring nodes. Therefore, an intermittent communication scheme is proposed among the follower agents as a consequence of employing the linear auxiliary dynamics. The closed-loop networked system signals are proved to be noise-to-state practically stable in probability (NSpS-P). It has been justified that each agent follows the trajectory of the corresponding local auxiliary virtual system practically in probability. The simulation experiments finally quantify the effectiveness of our proposed approach in terms of providing a resilient performance against unreliability of communication channels and reaching the tracking consensus.

Tracking Consensus of Networked Random Nonlinear Multi-agent Systems with Intermittent Communications

TL;DR

This work addresses tracking consensus for networks of followers with high-order nonlinear strict-feedback MASs in the presence of colored disturbances modeled as a wide stationary process . It introduces a linear auxiliary trajectory and an intermittent communication scheme with distributed virtual systems, and provides a Lyapunov-based analysis showing the closed-loop system is noise-to-state practically stable in probability (NSpS-P) and that agents track the leader within a bounded error. The design employs a stabilizable pair and a gain , along with neural-network based function approximation to handle unknown nonlinearities, and establishes resilience bounds on OFF-mode durations that guarantee eventual tracking consensus within . Simulation on a network of four agents demonstrates robust tracking under intermittent links and colored noise, highlighting the practical impact for resilient networked control systems.

Abstract

The paper proposes an intermittent communication mechanism for the tracking consensus of high-order nonlinear multi-agent systems (MASs) surrounded by random disturbances. Each collaborating agent is described by a class of high-order nonlinear uncertain strict-feedback dynamics which is disturbed by a wide stationary process representing the external noise. The resiliency level of this networked control system (NCS) to the failures of physical devices or unreliability of communication channels is analyzed by introducing a linear auxiliary trajectory of the system. More precisely, the unreliability of communication channels sometimes makes an agent incapable of sensing the local information or receiving it from neighboring nodes. Therefore, an intermittent communication scheme is proposed among the follower agents as a consequence of employing the linear auxiliary dynamics. The closed-loop networked system signals are proved to be noise-to-state practically stable in probability (NSpS-P). It has been justified that each agent follows the trajectory of the corresponding local auxiliary virtual system practically in probability. The simulation experiments finally quantify the effectiveness of our proposed approach in terms of providing a resilient performance against unreliability of communication channels and reaching the tracking consensus.
Paper Structure (7 sections, 2 theorems, 54 equations, 4 figures)

This paper contains 7 sections, 2 theorems, 54 equations, 4 figures.

Table of Contents

  1. Introduction
  2. Preliminaries and Problem Formulation
  3. Problem formulation
  4. Distributed Virtual Systems
  5. Design and Analysis
  6. Simulation results
  7. Conclusion

Key Result

Theorem 1

Under Assumption 1, consider the auxiliary trajectory of $i$-th agent in trajectory. Suppose that the data is intermittently transmitted among the agents according to the intermittent rule in Intermittentvirtualcontrol. Then, design the control gain $\bm{K} = c_{0} \bm{B}^{\rm {T}} \bm{P}$ for the o holds true, then the communication network is resilient to be switched to the OFF mode with a maxim

Figures (4)

  • Figure 1: Schematic time diagram for the intermittent communication operation modes.
  • Figure 2: The communication graph.
  • Figure 3: Consensus trajectory tracking: $\eta_{i,q}$ with respect to $z_{r}$ and $z_{r}^{\prime}$.
  • Figure 4: Consensus trajectory tracking: $x_{i,1}$ with respect to $z_{r}$.

Theorems & Definitions (4)

  • Theorem 1
  • proof
  • Theorem 2
  • proof