Identify flight control system based on least squares support vector machine

As flight control system is highly non-linear, it´s difficult to get desired results using traditional identification ways. And based on statistical learning theory, support vector machine, is considered a kind of new and feasible nonlinear system identification approach. In this paper, applied least square support vector regression machines and Series - Parallel identification model of system identification to identify flight control system model Through the simulation, the model of flight control system is successfully identified The simulation results show that: the design of the identification model predicted a good performance, with very high accuracy, at the same time; it also can be very good to reflect the characteristics of flight control systems.