Adaptive Neurocontrol of Simulated Rotor Vibrations Using Trailing Edge Flaps

Abstract

Smart structure activated trailing edge flaps are capable of actively altering the aerodynamic loads on rotor blades. Coupled with a suitable feedback control law, such actuators could potentially be used to counter the vibrations induced by periodic aerodynamic loading on the blades, without the bandwidth constraints and with a potential of lower weight penalties incurred by servo actuation methods. This paper explores new, robust individual blade control (IBC) methodologies for vibration suppression using a piezoactuated trailing edge flap. The controllers employ a single hidden layer neural network, learning in real time, to adaptively cancel the effects of periodic aerodynamic loads on the blades, greatly attenuating the resulting vibrations. Both collocated and noncollocated sensor/actuator pairs are considered. Proofs of the stability and convergence of the proposed neurocontrol strategies are provided, and numerical simulation results for a one-eighth Froude scale blade model are given which demonstrate that the controller can nearly eliminate the blade vibration arising from a wide variety of unknown, periodic disturbance sources.