Optimization via a Control-Centric Framework
This work creates a control-centric framework for designing optimization algorithms directly from Lyapunov stability principles. It introduces an Optimization Lyapunov Function (OLF) that encodes optimality conditions and allows engineers to select specific convergence rates, such as exponential or finite-time convergence. This unified approach applies to six problem classes, offering guaranteed performance across various dynamic regimes.