A Fixed-Time Distributed Resource Allocation Algorithm for Multi-Agent Systems with Actuator Faults

This paper studies a distributed algorithm that achieves fixed-time convergence and fault-tolerant optimization for the resource allocation problem of multi-agent systems with actuator faults. To address the impact of heterogeneous control gains caused by partial loss of effectiveness faults and unknown disturbances resulting from bias faults on system dynamics, an improved distributed weighted gradient algorithm is developed to achieve fault-tolerant optimization, based on output feedback and variable structure control methods. By utilizing convex optimization theory, fixed-time Lyapunov stability theory, and other tools, the stability of the proposed algorithm is analyzed, and sufficient conditions for achieving fixed-time optimal convergence are derived. Finally, simulation results validate the effectiveness of the proposed fault-tolerant optimization algorithm.