Design of Automatic Assembly System for Aircraft Control System Parts Based on Improved Genetic Algorithm

The traditional assembly process of aircraft control system parts is mostly manual. Due to human factors and the complexity of parts, the assembly quality and efficiency may be difficult to guarantee. Based on this, this article proposes a design strategy of automatic assembly system for aircraft control system parts based on improved genetic algorithm (IGA). Through experiments, it is found that, compared with traditional genetic algorithm (GA), IGA shows higher global searching ability and efficiency when dealing with automatic assembly and feature detection of aircraft control system parts, and avoids falling into local optimal solution prematurely, and its output results are more consistent with the actual results. These results show that IGA has higher applicability and efficiency in solving such complex optimization problems. To sum up, this article compares and analyzes the performance of IGA and traditional GA in automatic assembly and feature detection of aircraft control system parts, and verifies the superiority of IGA. These conclusions have certain guiding significance for further optimizing the application of GA and other fields.