Design of control law for ejection seat under adverse attitudes

The escape performance of ejection seat under adverse attitudes is the key technology for the 4th generation ejection seat, and the design of control law algorithm is the core problem for attitude and trajectory adjustment. A new control law design method was presented. Firstly, a simulation model for the entire ejecting process was established and a control parameter optimization model was designed, through which an optimum parameter set was obtained as the discrete control law. Then, by utilizing multi-layer feedback of the error back propagation (BP) algorithm based neural network model, the ultimate continuous control law can be acquired under the whole ejecting conditions. The roll attitude ejecting condition was exampled to design and validate the approached method. The results indicate that the performance of ejection seat by adopting the control law designed by the proposed method is higher than the multi-mode control law and the K36Л-3.5 ejection seat, which also satisfies the performance demand of GJB under most conditions. Consequently, the design method is simple and clear, and the final algorithm is close to the theoretical optimum result. Therefore, it is proved to be a useful method for the design of the 4th generation ejection seat control law.