Distributed Robust Continuous-Time Optimization Algorithms for Time-Varying Constrained Cost Functions

This paper presents a distributed continuous-time optimization framework aimed at overcoming the challenges posed by time-varying cost functions and constraints in multi-agent systems, particularly those subject to disturbances. By incorporating tools such as log-barrier penalty functions to address...

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Bibliographic Details
Published inInternational Conference on Control, Mechatronics and Automation (Online) pp. 7 - 13
Main Authors Ebrahimi, Zeinab, Deghat, Mohammad
Format Conference Proceeding
LanguageEnglish
Published IEEE 11.11.2024
Subjects
Convergence
Cost function
Distributed time-varying optimization
disturbances
Heuristic algorithms
Mechatronics
Multi-agent systems
Numerical simulation
Prevention and mitigation
Robustness
Sliding mode control
time-varying constraints
Time-varying systems
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Summary:This paper presents a distributed continuous-time optimization framework aimed at overcoming the challenges posed by time-varying cost functions and constraints in multi-agent systems, particularly those subject to disturbances. By incorporating tools such as log-barrier penalty functions to address inequality constraints, an integral sliding mode control for disturbance mitigation is proposed. The algorithm ensures asymptotic tracking of the optimal solution, achieving a tracking error of zero. The convergence of the introduced algorithms is demonstrated through Lyapunov analysis and nonsmooth techniques. Furthermore, the framework's effectiveness is validated through numerical simulations considering two scenarios for the communication networks.
ISSN:2837-5149
DOI:10.1109/ICCMA63715.2024.10843887