Abstract
This manuscript concentrates on the problem of designing a sampled data controller (SDC) for the consensus of a fractional-order multi-agent system (FOMAS) with Lipschitz non-linearity via an algebraic approach. The solution of the FOMAS is represented by using the Laplace transform approach. An upper bound of the sampling period is determined through various integral inequality techniques. Distinguished from the existing works, the estimate for an upper bound is more accurate which involves the Lipschitz constant of the non-linear function. Finally, numerical examples are given to validate the correctness of results. Furthermore, the comparison results are presented to show the proposed method determines a better upper bound of the sampling period.
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Research ethics: Not applicable.
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Author contributions: Padmaja N: Conceptualization, Writing-Initial Draft, Numerical Validation of Results. Balasubramaninam P: Writing-Review and Editing; Validation of Results. Lakshmanan S: Writing-Review and Editing; Validation of Results.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors declare that they have no conflicts of interest.
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Research funding: None declared.
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Data availability: The data presented in this study are available on request from the corresponding author. The data are not publicly available.
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© 2024 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Research Articles
- High-order approximation of Caputo–Prabhakar derivative with applications to linear and nonlinear fractional diffusion models
- Containment control for non-linear fractional-order multi-agent systems via refined sample data controller
- New Lyapunov stability theorems for fractional order systems
- Application of Chelyshkov polynomials in solving stochastic model with fractional Brownian motion
Articles in the same Issue
- Frontmatter
- Research Articles
- High-order approximation of Caputo–Prabhakar derivative with applications to linear and nonlinear fractional diffusion models
- Containment control for non-linear fractional-order multi-agent systems via refined sample data controller
- New Lyapunov stability theorems for fractional order systems
- Application of Chelyshkov polynomials in solving stochastic model with fractional Brownian motion