Distributed Predefined-Time Convergent Algorithm for Solving Time-Varying Resource Allocation Problem Over Directed Networks

Abstract

This article introduces an innovative distributed algorithm tailored for achieving predefined-time convergence in addressing time-varying resource allocation problem under directed networks. The attainment of predefined-time convergence is crucial for fulfilling real-time requirements, ensuring quality and safety standards, and optimizing the efficiency of resource utilization. It grants users the flexibility to tailor the convergence time according to their specific requirements and constraints. Moreover, the algorithm integrates an auxiliary system to ensure continual satisfaction of the global equality constraint. A distinctive feature lies in the utilization of nonhomogeneous functions with exponential terms, facilitating the achievement of predefined-time convergence. Compared to some existing algorithms with dynamic behaviors, including asymptotical convergence, exponential convergence, and fixed-time convergence, the proposed algorithm demonstrates superior convergence speed. Finally, we demonstrate the effectiveness of the designed technique through numerical simulations, comparisons with state-of-the-art algorithms, and its application to multienergy management problem in the multimicrogrid system.