Prescribed-time optimal resource allocation for disturbed multi-agent systems subject to limited interaction ranges

In practical multi-agent systems, limited interaction ranges give rise to state-dependent and dynamically evolving communication topologies, which poses a fundamental challenge for existing methods to achieve efficient optimization. This paper addresses prescribed-time distributed resource allocation for disturbed multi-agent systems operating under limited interaction ranges. A simplified connectivity-preserving mechanism is constructed to maintain network connectivity effectively. The proposed algorithm incorporates an innovative time-varying auxiliary function to handle the global supply-demand balance constraint. Furthermore, it integrates integral sliding mode control with time-based generators to achieve prescribed-time rejection of external disturbances and prescribed-time convergence to the optimal solution. Simulation results on IEEE bus systems and coupled-cost smart grids demonstrate the algorithm’s applicability to complex power system resource allocation.