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Finite and fixed-time feedback-based continuous-time optimization
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DOI：10.1016/j.automatica.2025.112569.png)
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Abstract
En 中文
This article presents a framework for finite and fixed-time control, using feedback-based optimization to drive a system toward its optimal operating point. Unlike traditional methods that rely on predefined set points, this approach employs endogenous control inputs derived through numerical optimization while adhering to system constraints. The controller’s dynamics are modeled as a convergent gradient flow, allowing the system to autonomously achieve its optimum without external references. The proposed control architecture guarantees finite- and fixed-time stability, with a Lyapunov-based analysis determining permissible perturbation bounds to ensure robust performance. The effectiveness of the proposed control strategy is demonstrated through simulations on a coupled-tank and a buck converter systems, successfully achieving the desired steady-state operation with the designed control approach.
Keywords:
Gradient flow system
Continuous-time optimization
Finite-time stability
Fixed-time stability
Journal
IF:
5.9
Papers:
1.2W
Citations:
5.2W