Engineering topics

Matthew L Wilbur

Publications and source records attributed to Matthew L Wilbur.

2 records

NASA NTRS2000

Hover Testing of the NASA/Army/MIT Active Twist Rotor Prototype Blade

Helicopter rotor individual blade control promises to provide a mechanism for increased rotor performance and reduced rotorcraft vibrations and noise. Active material methods, such as piezoelectrically actuated trailing-edge flaps and strain-induced rotor blade twisting, provide a means of accomplishing individual blade control without the need for hydraulic power in the rotating system. Recent studies have indicated that controlled strain induced blade twisting can be attained using piezoelectric active fiber composite technology. In order to validate these findings experimentally, a cooperative effort between NASA Langley Research Center, the Army Research Laboratory, and the MIT Active Materials and Structures Laboratory has been developed. As a result of this collaboration an aeroelastically-scaled active-twist model rotor blade has been designed and fabricated for testing in the heavy gas environment of the Langley Transonic Dynamics Tunnel (TDT). The results of hover tests of the active-twist prototype blade are presented in this paper. Comparisons with applicable analytical predictions of active-twist frequency response in hovering flight are also presented.

Matthew L Wilbur↗

NASA NTRSDate not supplied

Experimental Testing of Advanced Generalized Predictive Control for Stability Augmentation and Vibration Reduction of Tiltrotor Aircraft

Generalized Predictive Control (GPC) is an advanced form of an adaptive control algorithm that uses experimentally acquired data to determine the input-output relationship of complex systems through a process called system identification (system ID). GPC has historically been applied to wind tunnel tests of dynamically-scaled tiltrotor aircraft for stability augmentation and vibration reduction since the complex nature of these dynamic systems does not lend itself well to traditional control theory. Advanced GPC (AGPC) improves upon traditional GPC by enabling self-adaptation as conditions change from those used to acquire the system ID and controller performance would normally erode. The present research expands upon previous analytical development and demonstration of AGPC with experimental demonstration. To support AGPC, this present work also identifies and describes figures of merit that define a good working controller and quantifies the uniqueness of the control inputs and quality of the system ID parameters. The present research demonstrates that AGPC consistently performs better than traditional GPC and can successfully adapt to changing conditions.

Active Controls↗