Abstract: A system for collaboration and optimization of edge machines based on federated learning is provided. The system includes R federated learning systems, R?1, a model parameter assignment unit, and model training and optimizing units. The model parameter assignment unit is configured to assign initial parameters for federated learning to the Mi edge machines, receive intermediate model parameters, and aggregate and update the received intermediate model parameters to obtain new model parameters. The model training and optimizing units are configured to train, on the basis of the initial parameters and respective operating data, local operating models, transmit the intermediate model parameters obtained after training to the model parameter assignment unit, and obtain a system collaborative operating model according to the new model parameters.