Interval Uncertainty Optimization Method for Electromagnetic Orbital Launcher

• Published in: Applied sciences 2023-08, Vol.13 (15), p.8806
• Main Authors: Jin, Liang, Liu, Lu, Song, Juheng, Yan, Yingang, Zhang, Xinchen
• Format: Article
• Language: English
• Subjects: Algorithms; Composite materials; Design optimization; Distribution (Probability theory); Efficiency; electromagnetic orbital launcher; Electromagnetism; Genetic algorithms; interval number; Linear programming; Mathematical optimization; Methods; multi-objective optimization; Optimization algorithms; Powertrain; Probability distribution; uncertainty parameters; Variables
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app13158806

The performance optimization and reliability of electromagnetic orbital launchers need to take into account the uncertainties that exist in the manufacturing and service processes. Considering that it is difficult to identify the problem of the parameter probability distribution in advance for electromagnetic orbital launchers, this paper uses the interval number to describe the uncertain variables and realizes the conversion of uncertainty optimization into deterministic optimization problems based on interval sequential relations; moreover, it establishes interval uncertainty optimization methods. The converted deterministic optimization problem is solved by combining a high-precision proxy model with an optimization algorithm to search for the optimal solution set. Finally, reliability estimation is achieved by taking the armature of the electromagnetic orbital launcher as the optimization object. The computational example proves that the method is able to deal with the optimization problem of the parameter interval of an electromagnetic orbital launcher containing uncertain parameters and has good engineering applicability.