An Intermediate Observer‐Based Fault Estimation for Lipschitz Nonlinear Multi‐Agent Systems Subject to Switching Topologies

Multi‐agent systems operating in complex environments face challenges such as topology switching, nonlinear dynamics, multiple faults, and external disturbances. Traditional fault estimation methods often rely on strict observer matching conditions and exhibit poor adaptability to topology changes, leading to reduced estimation accuracy. To overcome these issues, this paper proposes a fault estimation algorithm based on an intermediate observer by leveraging the average dwell‐time technique and theory. First, an intermediate observer is designed by constructing an augmented state vector. An intermediate auxiliary variable is introduced using relative output estimation errors to eliminate the matching condition constraint. Second, the average dwell‐time technique is applied to analyze the stability conditions of the system under topology switching, and a minimum dwell‐time threshold is derived. Moreover, the performance criterion is incorporated into the observer gain design to suppress external disturbances and enhance the system's disturbance rejection capability. Finally, simulation results demonstrate that the proposed method achieves accurate fault estimation in the presence of switching topologies, nonlinearities, multiple faults, and external disturbances.