Distributed Continuous-Time Optimization with Time-Varying Objective Functions and Inequality Constraints

This paper is devoted to the distributed continuous-time optimization problem with time-varying objective functions and time-varying nonlinear inequality constraints. Different from most studied distributed optimization problems with time-invariant objective functions and constraints, the optimal so...

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Bibliographic Details
Published inProceedings of the IEEE Conference on Decision & Control pp. 5622 - 5627
Main Authors Sun, Shan, Ren, Wei
Format Conference Proceeding
LanguageEnglish
Published IEEE 14.12.2020
Subjects
Convex functions
Linear programming
Minimization
Optimization
Resource management
Sun
Trajectory
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Summary:This paper is devoted to the distributed continuous-time optimization problem with time-varying objective functions and time-varying nonlinear inequality constraints. Different from most studied distributed optimization problems with time-invariant objective functions and constraints, the optimal solution in this paper is time varying and forms a trajectory. To minimize the global time-varying objective function subject to time-varying local constraint functions using only local information and local interaction, we present a distributed control algorithm that consists of a sliding-mode part and a Hessian-based optimization part. The asymptotical convergence of the proposed algorithm to the optimal solution is studied under suitable assumptions. The effectiveness of the proposed scheme is demonstrated through a simulation example.
ISSN:2576-2370
DOI:10.1109/CDC42340.2020.9304273