Artillery structural dynamic responses uncertain optimization based on robust Nash game method

To coordinate the contradiction between artillery launching performance indexes under parameter uncertainty, this paper proposes an artillery structural dynamic responses optimization method based on robust Nash game theory. First, a multi-flexible body dynamic model for a 155 mm caliber artillery is established, which coupling the interior ballistic model, recoil force model, and balance mechanism model. Secondly, the live firing experiment is carried out to verify the accuracy of the established multi-flexible model. Then the muzzle vibration and maximum chamber pressure are selected as the players in the game. Because these two indexes can represent the most critical contradictory indexes of artillery, namely the firing accuracy and power. Afterward, to reduce the computational time, the BP neural network surrogate model is constructed to replace the original multi-flexible body dynamic model. Finally, the double-loop approach is adopted to search for the robust Nash equilibrium. The inner loop optimization is used to determine the worst-case scenario caused by the parameter uncertainty. The outer loop optimization is referred to as the robust Nash equilibrium solution process. The results show that the artillery structural dynamics responses have been significantly improved.