Robust Control for Aircraft with Reaction Jets Using Dynamic Inversion and Fuzzy Neural Networks

In this study, a robust control scheme based on dynamic inversion using fuzzy neural networks (FNN) is designed to control a nonlinear aircraft driven by two different actuators (fins and reaction jets). First, the dynamic model of the aircraft with reaction jets is briefly introduced. Then, the robust control scheme is explained in detail, in which the dynamic inversion is adopted to solve the system nonlinearity and the FNN cancels model uncertainties by on-line learning. Learning is accomplished by a simple weight update rule derived from Lyapunov theory, thus assuring the stability of the closed loop system. In addition, a control moment allocator is designed to coordinate the work of fins and reaction jets. Finally, the control scheme is demonstrated in simulation. Its robustness is evaluated relative to a PID control based on dynamic inversion; its rapid time response performance is compared with a conventional aircraft with fins only, to certify the effectiveness of the control moment allocator.