Research Area : Intelligent
Flight Control
The attributes of systems requiring
intelligent as opposed to conventional control include a high degree
of complexity, modeling uncertainty, and unpredictability of the
environment in which the system exists. Flight control systems for
the aerospace vehicles of the future are required to deal with
several advanced scenarios, including increasingly complex dynamical
systems; highly stringent performance requirements; less a priori
knowledge about the dynamical characteristics of the system; and
autonomous operations where the control system has
the ability to repair and reconfigure
itself to manage unpredictable scenarios and changing performance
requirements.
Intelligent flight
control and its variations are applicable to a wide class of
applications that are of interest to NASA, the Department of
Defense, the Department of Transportation, and various other
governmental and nongovernmental organizations. These applications
include control of high-performance aircraft, spacecraft and
aircraft formation flying, uninhabited air vehicles (UAVs),
uninhabited combat air vehicles (UCAVs), NASA Space Station
Telerobotics, etc. Intelligent flight control techniques include
neural-network application, adaptive control, fuzzy-logic-based
control structured in some hierarchical fashion.
The
research in this area will be organized in terms of the activities
described below:
Research Activity: Control of
High-Performance Air Vehicles
"High-performance air
vehicle" refers to aircraft flying at extremely high altitudes and
velocities, such as the x-43, NASA's experimental hypersonic
vehicle, and the class of future combat aircraft with extreme
performance and maneuverability requirements. Future combat
aircraft will be expected to maintain their flight control
properties despite significant levels of uncertainty, classes of
subsystem failures and battle damage, and large unanticipated
disturbances. A highly integrated modeling approach and advanced
methodologies will be required to design and analyze control systems
with enhanced capabilities and performance for these air vehicles.
The solution to the control problem in this case will depend on a
combination of approaches and techniques and a good understanding of
the model and performance requirements. Some of the approaches and
control techniques include: Robust Adaptive Control Techniques; Neuro-Adaptive Control Techniques; Nonlinear Control Techniques;
Integrated Control Approach; Hybrid Control Analysis.
Research Activity: Failure Detection, Isolation, and Reconfiguration
As previously indicated,
future high-performance aircraft will be expected to operate outside
currently achievable flight envelopes, pushing their performance
closer to possible performance limits. They will be expected to
maintain their flight control properties in the presence of
significant levels of uncertainty, classes of subsystem failures,
battle damage, and large unanticipated
disturbances. Research will be conducted to
design and analyze a robust adaptive fault-tolerant control (RAFTC)
system capable of dealing with such uncertainties. Some of the main
attributes of the RAFTC system that the Investigators will develop
are detectability/isolability, sensitivity, robustness, adaptivity,
reconfigurability, and restructurability. The techniques developed will be analyzed and tested for use in
high-performance aircraft, spacecraft, and UAVs.
The following specific research tasks will be investigated: Severe
Single and Multiple Failures; Sensitivity; Tests and Simulations.
Nonlinear models of high-performance aircraft will be used to
demonstrate the RAFTC system under different critical maneuvers,
failures, and parametric uncertainties.
