Abstract:
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. GPC has historically been employed for stability augmentation and vibration reduction of dynamically-scaled tiltrotor aircraft wind-tunnel models since the complex nature of these dynamic systems does not lend itself well to traditional control approaches. The present research expands upon previous analytical and experimental work with wind-tunnel experiments that utilize improved GPC techniques. These techniques improved controller robustness such that a working controller was stable across a multitude of model configurations and wind-tunnel conditions and successfully suppressed vibration and vehicle flutter. Advanced GPC (AGPC) enables self-adaptation of a traditional GPC control law. AGPC was also investigated during the present research but was not needed as anticipated because of the robustness resulting from improvements made to traditional GPC.