Abstract
Skimming the sea at ultralow altitudes can be achieved by repeatedly touching and bouncing off water surface (commonly referred to as skipping), thus giving birth to skippable anti-ship missiles. However, the high impact load during skipping poses a safety hazard to the structure. Whether a missile can rebound primarily depends on the initial kinematic parameters, which also influence the impact load along with the configuration parameters. Therefore, it is important to optimize both of them. Due to the differences in types and complicated coupling of these parameters, the optimization problem becomes highly complex. In this paper, the grouped sequential quadratic programming (GSQP) algorithm is proposed to reduce the nonlinearity and nonconvexity of the problem. By bringing together the global search capability of cooperative co-evolutionary algorithm and the local search strength of GSQP, a combined optimization framework using decomposition strategies is constructed. With the support of fluid–structure interaction models, the optimization is performed to reduce impact load for the missile. The results demonstrate that simultaneously optimizing the configuration and initial kinematic parameters yields a reduction of 12.2% in the impact load on the premise of successful skipping. This research provides a valuable reference for the design of future skippable anti-ship missiles.
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