Advanced Guidance and Control Methods for Reusable Launch Vehicles: Test Results

Hanson, John M.; Jones, Robert E.; Krupp, D.; Fogle, Frank R.

doi:10.2514/6.2002-4561

Cited by 33 publications

(32 citation statements)

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“…This problem is also of great interest for reusable launch vehicles, and different approaches have been examined [78]. Recently, Barron associates flight tested an approach for this on the TIFS aircraft, which was being used to simulate an X-40 testbed [84].…”

Section: Beyond the Inner Loopmentioning

confidence: 99%

“…In the study led by NASA, Marshall looked at a Reusable Launch Vehicle reconfiguration and trajectory optimization problem based on an X-33 simulation model [78]. The inner loop approaches included a sliding mode controller, an adaptive neural-network approach, a dynamic inversion controller, a linear parametrically varying controller, and control design by trajectory linearization.…”

Section: Fig 5 Adaptive Neural Network Flight Tested On X-36mentioning

confidence: 99%

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Historical Overview of Research in Reconfigurable Flight Control

Steinberg

2005

Proceedings of the Institution of Mechanical Engineers, Part G:

113

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This article presents a historical overview of research in reconfigurable flight control. For the purpose of this article, the term 'reconfigurable flight control' is used to refer to software algorithms designed specifically to compensate for failures or damage of flight control effectors or lifting surfaces, using the remaining effectors to generate compensating forces and moments. This article will discuss initial research and flight testing of approaches based on explicit fault detection, isolation, and estimation, as well as later approaches based on continuously adaptive and intelligent control algorithms. In addition, approaches for trajectory reshaping of an impaired aircraft with reconfigurable inner loop control laws will be briefly discussed. Finally, there will be some discussion on current implementations of reconfigurable control to improve safety on production and flight test aircraft and remaining challenges to enable broader use of the technology, such as the difficulties of flight certification of these types of approaches.

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Section: Beyond the Inner Loopmentioning

confidence: 99%

Section: Fig 5 Adaptive Neural Network Flight Tested On X-36mentioning

confidence: 99%

Historical Overview of Research in Reconfigurable Flight Control

Steinberg

2005

Proceedings of the Institution of Mechanical Engineers, Part G:

113

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“…The heading error to HAC is defined as the difference between the heading of the vehicle and the required heading to be directed to the HAC point. Hanson and Jones 19 provide error tolerances for the TAEM point conditions, which are also presented in the Performance Assessment section of this paper.…”

Section: Entry Guidance Target Conditionsmentioning

confidence: 99%

Design and Evaluation of an Acceleration Guidance Algorithm for Entry

Saraf

Leavitt

Chen

et al. 2003

AIAA Guidance, Navigation, and Control Conference and Exhibit

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The design and performance evaluation of an entry guidance algorithm for future space transportation vehicles is presented. The guidance concept is to plan and track aerodynamic acceleration. This concept, on which the longitudinal entry guidance for the Space Shuttle Orbiter is based, is extended to integrated longitudinal and lateral guidance. With integrated longitudinal and lateral guidance, more extreme points in the landing footprint can be reached accurately; in particular, the cross-range capability is extended. The guidance algorithm consists of two components: a trajectory planner and a trajectory tracking law. The planner generates reference drag acceleration and heading angle profiles, along with reference state and bank angle profiles. The planner executes onboard and is capable of generating updates as the entry evolves. The tracking law, based on feedback linearization, commands the angles of bank and attack required to follow the reference drag and heading angle profiles. The planner and tracking law are described, along with additional higher level logic included in the algorithm. Extensive simulations for a set of return-from-orbit entries, including ones requiring large cross range, demonstrate that this algorithm consistently achieves the desired target conditions within allowable tolerances and satisfies all other entry constraints.Nomenclature A = reference wing area, ft 2 a max = maximum allowable normal acceleration, ft/s 2 a n = normal acceleration, ft/s

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“…Please refer to Ref. [5] for information regarding these cases. The control and state profiles of the trajectories used to create the EG17 to EG21 footprints are very similar to those for EG16.…”

Section: B Footprint With Varying Angle Of Attack Profilementioning

confidence: 99%

“…A 3 degree of freedom model of the X-33 vehicle is used for the landing footprint computations. A dispersed entry condition for case EG16 of NASA's Advanced Guidance and Control (AGC) study 5 has been used for all of the figures that precede this section. This trajectory corresponds to an early entry from the International Space Station orbit with an inclination of 51.6 deg.…”

Section: B Footprint With Varying Angle Of Attack Profilementioning

confidence: 99%

Landing Footprint Computation for Entry Vehicles

Saraf

Leavitt

Mease

et al. 2004

AIAA Guidance, Navigation, and Control Conference and Exhibit

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A method is developed for generating landing footprints for entry vehicles in near realtime, as needed for an on-board flight management system. The method described in the paper is built around a previously developed, acceleration-based trajectory planner. The boundary of the footprint is constructed from the endpoints of extreme downrange or crossrange trajectories generated by the planner. The strengths of the method include fast computation time, respecting path constraints such as vehicle heating limits, accounting for Coriolis effects and constructing angle of attack profiles that are nearly optimal for long range glide. The accuracy of the landing footprint generator is determined by direct comparison with footprints computed with a general purpose optimization program.

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Advanced Guidance and Control Methods for Reusable Launch Vehicles: Test Results

Abstract: There are a number of approaches to advanced guidance and control (

Cited by 33 publications

References 1 publication

Historical Overview of Research in Reconfigurable Flight Control

Historical Overview of Research in Reconfigurable Flight Control

Design and Evaluation of an Acceleration Guidance Algorithm for Entry

Landing Footprint Computation for Entry Vehicles

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