As the functionality of oscilloscopes continues to expand, their operational complexity has correspondingly increased, posing a significant learning barrier for novice users. Even those with basic operational knowledge often struggle to fully utilize the advanced features. To reduce the operational complexity of oscilloscopes, this study proposes an intelligent control system for oscilloscopes based on the large language model. Firstly, the system employs a domain adaptation technique by constructing a structured knowledge graph for oscilloscope control to generate domain-optimized prompts, thereby enhancing the large language model′s ability to comprehend user instructions. Secondly, the system incorporates semantic retrieval techniques, utilizing vector space modeling and approximate nearest neighbor search to filter the most relevant knowledge fragments from the knowledge graph based on user instructions. This approach compresses the prompt size and improves inference efficiency. Finally, by integrating these two techniques, the system establishes a closed-loop control mechanism of “an natural language instruction-standard commands for programmable instruments-operational feedback”, enabling precise control of the full range of oscilloscope functions through natural language. Experimental results demonstrate that on a self-constructed dataset, compared to directly using a large language model to generate standard commands for programmable instruments, the generation accuracy of the qwen-max-latest model improved from 6.20% to 99.6% after applying the domain adaptation technique. Furthermore, compared to using only domain adaptation, the incorporation of semantic retrieval technique, when running the qwen2.5-32b-instruct model on a single NVIDA RTX 4090 GPU, reduced average inference latency from 296 s to 23.3 s, while maintaining a loss inference accuracy of less than 7%. In summary, the intelligent oscilloscope control system proposed in this study effectively lowers the barrier to using oscilloscopes, provides technical support for the intelligent and automated operation of laboratory instruments, and demonstrates promising application prospects.