This article investigates the optimal resource allocation of nonlinear high-order multi-agent systems with coupling uncertainties. The objective is to design an output-feedback distributed algorithm for each agent to optimize the global cost function under network constraints. The global cost function is the sum of local cost functions. The available information to design the algorithm for each agent is only its own output and cost function, the outputs of its neighbors. To address the key technical challenge arising from the uncertainties and nonlinearities of network systems, a novel distributed resource allocation algorithm is proposed using active disturbance rejection strategy. The simulation results in the economic dispatch of a smart grid validate the effectiveness of the proposed method.

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