Intelligent Flight Control
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.
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