Neural network control in active vortex control based on low aspect ratio flying wing

A low aspect ration flying wing aircraft was researched. Full state feedback controller was used for the continuous control effectors to improve the stability of aircraft. To improve the control ability, a vortex flow controller (bang-bang controller) based on three layers BP neural network was used. Through adjust weights for states and the number of hidden layers, the designer could optimize the network. The convergence speed and precision of the network were improved by using variety step network. The evaluation criteria consist of closed-loop system performance and activity level of the vortex flow controller nozzles were given. The results show that application of a neural network controller improves general performance of regular design and makes controlling of the vortex flow controller activity more practical comparing to conventional controller.