Research on helicopter autorotation landing manipulation strategy based on PSO-LSSVM

This paper addresses the issue of safe flight following helicopter engine failure and proposes a phased prediction method for the pilot’s manipulation strategy during autorotation landing, based on PSO-LSSVM (Particle Swarm Optimization-Least Squares Support Vector Machine). Driven by flight simulator data, this method leverages the fast learning speed and strong generalization ability of the Least Squares Support Vector Machine (LSSVM) and combines it with the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the LSSVM. Ultimately, a pilot manipulation behavior model is established. Validation results indicate that this method has a certain level of reliability and can assist pilots in achieving a safe landing in emergency situations.