Bingyan Teng ^*

• Nanjing Institute of Technology Industrial Center, Qixia, China

Machine failures and changes in material information and other factors have led to excessive uncertainty in modern manufacturing systems. In addition, the conflicts in organizational production patterns brought about by economic and technological development have further made the perception of workshop disturbances in manufacturing systems more prominent. To further enhance the adaptability of manufacturing systems, a control technique based on recursive control structure is proposed, which introduces immune working mechanism to design the framework network of multi-agent manufacturing systems. At the same time, a negative selection algorithm is used to construct an antibody training system that considers perturbation problems. The results indicate that immune sensing nodes can effectively monitor manufacturing systems, with a decrease in false alarm rates of over 4%. The completion time and equipment load improvement demonstrated by the research model in scheduling experiments are 3.29% and 12.38%, and the production balance rate optimization exceeds 90%, far exceeding the results of traditional scheduling schemes, greatly improving the adaptive control ability of manufacturing system production. The regulatory ideas proposed in the study can provide reference and assistance for the improvement of industrial production intelligence and the establishment of sustainable economic systems.