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Fixed-Time Gradient Dynamics With Time-Varying Coefficients for Continuous-Time Optimization
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DOI：10.1109/TAC.2022.3206251.png)
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Abstract
En 中文
In this article, we propose fixed-time gradient dynamics with time-varying coefficients for continuous-time optimization. We first investigate the Lyapunov stability conditions that allow us to achieve fixed-time stability of the time-varying dynamical systems. We then use them to deal with continuous-time optimization problems. We show that under the proposed fixed-time gradient dynamics and by choosing time-varying coefficients, the searching trajectories converge to their optima in fixed-time from any initial points with a very fast rate. Simulation results are given to show the effectiveness of the proposed fixed-time gradient dynamics with tunable time-varying coefficients for continuous-time optimization.
Keywords:
Continuous-time optimization
fixed-time convergence
gradient-based method
Lyapunov function
Newton-like method
stability
time-varying systems
Journal
IF:
7
Papers:
1.3W
Citations:
6.7W
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