AIAA Guidance, Navigation, and Control Conference 2009
DOI: 10.2514/6.2009-5738
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L1 Adaptive Control Design for NASA AirSTAR Flight Test Vehicle

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Cited by 97 publications
(65 citation statements)
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“…These capabilities enable off-nominal conditions mitigation, upset prevention, and safe maneuvering and landing of the aircraft. Some recent research accomplishments in effectively mitigating vehicle failure and damage effects using adaptive control techniques are described in References [8] and [9], and recent results on trajectory generation and guidance under off-nominal conditions are given in References [10], [11], and [12]. Moreover, utilization of key flight safety components as control objectives would explicitly provide some measure of flight safety assurance through the resilient control function.…”
Section: B Resilient Guidance and Controlmentioning
confidence: 99%
“…These capabilities enable off-nominal conditions mitigation, upset prevention, and safe maneuvering and landing of the aircraft. Some recent research accomplishments in effectively mitigating vehicle failure and damage effects using adaptive control techniques are described in References [8] and [9], and recent results on trajectory generation and guidance under off-nominal conditions are given in References [10], [11], and [12]. Moreover, utilization of key flight safety components as control objectives would explicitly provide some measure of flight safety assurance through the resilient control function.…”
Section: B Resilient Guidance and Controlmentioning
confidence: 99%
“…The L 1 adaptive control architecture and its variants have been verified for a number of systems: flight tests of augmentation of an off-the-shelf autopilot for path following [8,9], autopilot design and flight test for Micro Air Vehicles (MAV) [10], tailless unstable military aircraft [11], Aerial Refueling Autopilot design [12,13], flexible aircraft (Sensorcraft) [14], control of wingrock in the presence of faults [15], air-breathing hypersonic vehicles [16], and the NASA AirSTAR Generic Transport Model [17].…”
Section: Adaptive Control Overviewmentioning
confidence: 99%
“…Also, care needs to be exercised when scheduling with respect to a state variable that changes rapidly. To overcome the limitations of linearity, much work has been done on nonlinear control law design, such as by dynamic inversion [5] and a host of adaptive techniques [6,7]. These are also not necessarily problem-free, with issues such as robustness to model uncertainty and stability guarantees requiring special attention.…”
Section: Introductionmentioning
confidence: 99%