Adaptive neurocontrol of simulated rotor vibrations using trailing edge flaps

Smart structure activated trailing edge flaps are capable of actively alter ing the aerodynamic lends on rotor blades. Coupled with a suitable feedback control law, such actuators could potentially be used to counter the vibra tions induced by periodic aerodynamic loading on the blades, without the ba ndwidth constraints and with a potential of lower weight penalties incurred by servo actuation methods. This paper explores new, robust individual bla de control (IBC) methodologies for vibration suppression using a piezoactua ted trailing edge flap. The controllers employ a single hidden layer neural network, learning in real time, to adaptively cancel the effects of period ic aerodynamic loads on the blades, greatly attenuating the resulting vibra tions. Both collocated and noncollocated sensor/actuator pairs are consider ed. Proofs of the stability and convergence of the proposed neurocontrol st rategies are provided, and numerical simulation results for a one-eighth Fr oude 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.