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Cooperative fixed-time/finite-time distributed robust optimization of multi-agent systems

Firouzbahrami, M ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1016/j.automatica.2022.110358
  3. Publisher: Elsevier Ltd , 2022
  4. Abstract:
  5. A new robust continuous-time optimization algorithm for distributed problems is presented which guarantees fixed-time convergence. The algorithm is based on a Lyapunov function technique and applied to a class of problems with coupled local cost functions. The algorithm applies a methodology with no expansion of the local variables. This reduces the computation complexities of the solution and improves scalability. Using an integral sliding mode strategy we incorporate effective disturbances rejection on the decision variables as experienced in a wide range of industrial applications. It is shown that the algorithm can easily be modified to a finite-time solution when evaluations of the optimization variables are required to be bounded. Two illustrative examples with different simulation scenarios are considered to study the effectiveness of the results. © 2022 Elsevier Ltd
  6. Keywords:
  7. Coupled cost functions ; Disturbance rejection ; Continuous time systems ; Convex optimization ; Lyapunov functions ; Multi agent systems ; Continuous-time optimization ; Convex optimisation ; Cost-function ; Coupled cost function ; Distributed convex optimization ; Finite-time ; Finite-time convergence ; Fixed time ; Fixed-time/finite-time convergence ; Robust optimization ; Cost functions
  8. Source: Automatica ; Volume 142 , 2022 ; 00051098 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0005109822002084