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Cited by 199

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Two Reconfigurable Flight-Control Design Methods: Robust Servomechanism and Control Allocation

Open access
Burken, John J., Lu, Ping, Wu, Zhenglu, Bahm, Cathy·2001·Journal of Guidance, Control, and Dynamics

Abstract

Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the fight body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.

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Metadata

Authors
Burken, J. J., Lu, P., Wu, Z., & Bahm, C.
Venue
Journal of Guidance, Control, and Dynamics
Published
2001-05
Volume
24
Issue
3
Pages
482-493
ISSN
  • 0731-5090 (ISSN-L)
  • 1533-3884
OpenAlex
W2064591510
Cited by
199
References
0
FWCI
16.04
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Two Reconfigurable Flight-Control Design Methods: Robust Servomechanism and Control Allocation. https://app.cochat.ai/papers/10.2514/2.4769
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Burken, J. J., Lu, P., Wu, Z., & Bahm, C. (2001). Two Reconfigurable Flight-Control Design Methods: Robust Servomechanism and Control Allocation. Journal of Guidance, Control, and Dynamics. https://doi.org/10.2514/2.4769

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.