Distributed convex optimization based on zero‐gradient‐sum algorithm under switching topology
This paper designs a finite‐time convergence protocol and an event‐triggered control protocol based on Zero‐Gradient‐Sum (ZGS) algorithm under stochastic switching undirected topology, respectively, which greatly expands the theory of continuous‐time distributed optimization algorithms. With finite‐...
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| Published in | IET control theory & applications Vol. 17; no. 12; pp. 1611 - 1624 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Stevenage
John Wiley & Sons, Inc
01.08.2023
Wiley |
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| Online Access | Get full text |
| ISSN | 1751-8644 1751-8652 1751-8652 |
| DOI | 10.1049/cth2.12497 |
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| Abstract | This paper designs a finite‐time convergence protocol and an event‐triggered control protocol based on Zero‐Gradient‐Sum (ZGS) algorithm under stochastic switching undirected topology, respectively, which greatly expands the theory of continuous‐time distributed optimization algorithms. With finite‐time stability and Lyapunov stability analysis, it is illustrated that the proposed method can finite‐time converge to the optimal solution of distributed unconstrained convex optimization problem and overcome the disturbances of the switching communication networks. In addition, the event‐triggered mechanism can effectively reduce the network burden and communication cost as well as avoid Zeno behaviour. Finally, two numerical simulations verify the advantages and effectiveness of these methods.
This paper designs a finite‐time convergence protocol and an event‐triggered control protocol based on Zero‐Gradient‐Sum (ZGS) algorithm under stochastic switching undirected topology, respectively, which greatly expands the theory of continuous‐time distributed optimization algorithms. With finite‐time stability and Lyapunov stability analysis, it is illustrated that the proposed method can converge to the optimal solution of distributed unconstrained convex optimization problem and overcome the disturbances of the switching communication networks. |
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| AbstractList | Abstract This paper designs a finite‐time convergence protocol and an event‐triggered control protocol based on Zero‐Gradient‐Sum (ZGS) algorithm under stochastic switching undirected topology, respectively, which greatly expands the theory of continuous‐time distributed optimization algorithms. With finite‐time stability and Lyapunov stability analysis, it is illustrated that the proposed method can finite‐time converge to the optimal solution of distributed unconstrained convex optimization problem and overcome the disturbances of the switching communication networks. In addition, the event‐triggered mechanism can effectively reduce the network burden and communication cost as well as avoid Zeno behaviour. Finally, two numerical simulations verify the advantages and effectiveness of these methods. This paper designs a finite‐time convergence protocol and an event‐triggered control protocol based on Zero‐Gradient‐Sum (ZGS) algorithm under stochastic switching undirected topology, respectively, which greatly expands the theory of continuous‐time distributed optimization algorithms. With finite‐time stability and Lyapunov stability analysis, it is illustrated that the proposed method can finite‐time converge to the optimal solution of distributed unconstrained convex optimization problem and overcome the disturbances of the switching communication networks. In addition, the event‐triggered mechanism can effectively reduce the network burden and communication cost as well as avoid Zeno behaviour. Finally, two numerical simulations verify the advantages and effectiveness of these methods. This paper designs a finite‐time convergence protocol and an event‐triggered control protocol based on Zero‐Gradient‐Sum (ZGS) algorithm under stochastic switching undirected topology, respectively, which greatly expands the theory of continuous‐time distributed optimization algorithms. With finite‐time stability and Lyapunov stability analysis, it is illustrated that the proposed method can finite‐time converge to the optimal solution of distributed unconstrained convex optimization problem and overcome the disturbances of the switching communication networks. In addition, the event‐triggered mechanism can effectively reduce the network burden and communication cost as well as avoid Zeno behaviour. Finally, two numerical simulations verify the advantages and effectiveness of these methods. This paper designs a finite‐time convergence protocol and an event‐triggered control protocol based on Zero‐Gradient‐Sum (ZGS) algorithm under stochastic switching undirected topology, respectively, which greatly expands the theory of continuous‐time distributed optimization algorithms. With finite‐time stability and Lyapunov stability analysis, it is illustrated that the proposed method can converge to the optimal solution of distributed unconstrained convex optimization problem and overcome the disturbances of the switching communication networks. This paper designs a finite‐time convergence protocol and an event‐triggered control protocol based on Zero‐Gradient‐Sum (ZGS) algorithm under stochastic switching undirected topology, respectively, which greatly expands the theory of continuous‐time distributed optimization algorithms. With finite‐time stability and Lyapunov stability analysis, it is illustrated that the proposed method can finite‐time converge to the optimal solution of distributed unconstrained convex optimization problem and overcome the disturbances of the switching communication networks. In addition, the event‐triggered mechanism can effectively reduce the network burden and communication cost as well as avoid Zeno behaviour. Finally, two numerical simulations verify the advantages and effectiveness of these methods. |
| Author | Tan, Manchun Xiang, Jianglian Ren, Junwu Ye, Lei |
| Author_xml | – sequence: 1 givenname: Manchun orcidid: 0000-0002-9459-668X surname: Tan fullname: Tan, Manchun email: tanmc@jnu.edu.cn organization: Jinan University – sequence: 2 givenname: Junwu orcidid: 0000-0001-7563-3505 surname: Ren fullname: Ren, Junwu organization: Jinan University – sequence: 3 givenname: Lei surname: Ye fullname: Ye, Lei organization: Jinan University – sequence: 4 givenname: Jianglian surname: Xiang fullname: Xiang, Jianglian organization: Jinan University |
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| SubjectTerms | Algorithms asymptotic stability Communication Communication networks Communications networks continuous time systems Control algorithms convergence Convex analysis Convexity Cost analysis distributed algorithms Network topologies Optimization algorithms Stability analysis Sums Switching Topology optimization |
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| Title | Distributed convex optimization based on zero‐gradient‐sum algorithm under switching topology |
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