Distributed Average Consensus of Stochastic Singularly Perturbed Systems

The distributed consensus problems for singularly perturbed multiagent systems with noise are discussed in this study. By implementing Kalman-Bucy filtering when the communication topology satisfies connectivity conditions, the suggested protocol can produce a bounded average consensus. The benefit of such a protocol is that it helps to eliminate the ill-conditioning of solitary perturbation in systems and prevents the use of erroneous local information regarding the interconnection among agents in systems. The two main difficulties are designing control protocols using Kalman-Bucy filtering and decoupling using separation techniques. In particular, the convergence rate is examined along with <inline-formula><tex-math notation="LaTeX">$\varepsilon$</tex-math></inline-formula>-average consensus and <inline-formula><tex-math notation="LaTeX">$\varepsilon$</tex-math></inline-formula>-a.s. average consensus. By using numerical examples, theoretical analysis can be demonstrated.

• Publication year

  2023

• Venue

  IEEE Transactions on Control of Network Systems

• Publication date

  2023-12-01

• Fields of study

  Mathematics, Computer Science, Engineering

• Identifiers
  DOI 10.1109/TCNS.2023.3256271
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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