Neural　network　gain scheduling　design for large envelope curve flight control law

A 3-layer BP(back propagation) network is developed for the gain scheduling flight control law in a large flight envelope curve for a flight by wire flight control system. It can replace the traditional gain scheduling according to the altitude, Mach number or dynamical pressure which is only one-parameter adjusting and then difficult to find the adjust rule and so the stability in hole flight envelope curve, specially for those flight conditions between the designed points, can’t be guaranteed. The design procedure included choosing a BP network with middle layer of 6 points only and its parameter train. The outputs are the designed optimal robust 8 feedback gains. This network realized double parameters (altitude and Mach) gain adjusting. The illustration shows the neural network can give the same control parameters at the designed flight conditions and then the response can be the same good as before. It gets a good control effect at other un-designed flight conditions, also for the system with about 50% dynamical modeling error. It gives more finely carve up result of the control parameters between all flight conditions and shows a strong extrapolate ability.