Lightweight and high-performance aluminum alloys are crucial for the weight reduction design of aerospace equipment, thus spray forming with rapid solidification technology has garnered increasing attention for the fabrication of high-strength aluminum alloys. To meet the demands of large-scale aerospace components, a multi-nozzle collaborative system is required to achieve larger billet diameters. During the scanning and deposition process of atomization cones formed by multiple nozzles at a certain inclination angle on the deposition interface, ensuring uniform distribution of the molten material, a flat deposition interface at the top of the billet, and stable growth are key to obtaining high-quality, dense, and uniform deposited billet structures. These factors are key to producing high-quality billets with dense and uniform microstructures. The process parameters associated with multi-nozzle configurations directly influence the scanning trajectories of atomized droplets and the material deposition state at the interface, playing a decisive role in billet growth. Accordingly, by targeting the fabrication of large-size billets with consistent surface morphology and uniform deposition quality, a multi-nozzle deposition surface behavior model (DSBM) at the micro-scale was established based on the scanned deposition height, taking into account the overlap and intersection of deposition regions that arise during scanning of the multi-nozzle atomization cones. The initial nozzle tilt angle, nozzle eccentric offset, and melt mass flow rate were selected as adjustable parameters; constraints were set according to the actual operating conditions to construct a DSBM-based control model. Using the height difference H of the billet’s deposition-surface unevenness as the optimization objective, the GA-DSBM intelligent control method for the deposition interface was employed to simulate and optimize the relevant process para-meters during deposition. A four-nozzle spray-forming experiment was conducted to verify the optimized parameters. The resulting billet, with a diameter of 600 mm, exhibited a surface unevenness height difference of 7.52 mm, meeting the process design requirements. Meanwhile, the top-surface unevenness of the billet was markedly reduced, interfacial material uniformity was improved, and the billet porosity was effectively lowered—thereby validating the feasibility of the proposed intelligent control and optimization method.