2016
DOI: 10.1007/s11432-016-0169-8
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L 1 adaptive control of a generic hypersonic vehicle model with a blended pneumatic and thrust vectoring control strategy

Abstract: The extreme aeroheating at hypersonic regime and the insufficient dynamic pressure in the near space limit the achievable performance of the hypersonic vehicles using aerosurfaces alone. In this paper, an integrated pneumatic and thrust vectoring control strategy is employed to design a control scheme for the longitudinal dynamics of a hypersonic vehicle model. The methodology reposes upon a division of the model dynamics, and an L 1 adaptive control architecture is applied to the design of the inner-loop and … Show more

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Cited by 6 publications
(2 citation statements)
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“…In addition, model uncertainties and measurement errors may also seriously affect the control accuracy [19]. Compared to other control methods, adaptive control is relatively model-free and its addition can compensate for the effects of possible faults or unexpected uncertainties and achieve a substantial improvement in performance; however, it is difficult for conventional adaptive control methods to achieve the trade-off between control performance and robustness [20][21][22]. L 1 adaptive control, an improvement of model reference adaptive control (MRAC) presented by Cao and Hovakimyan, appears to be beneficial both for robustness and performance [22][23][24], resolving the trade-off between the two by selecting a low-level filtering structure.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, model uncertainties and measurement errors may also seriously affect the control accuracy [19]. Compared to other control methods, adaptive control is relatively model-free and its addition can compensate for the effects of possible faults or unexpected uncertainties and achieve a substantial improvement in performance; however, it is difficult for conventional adaptive control methods to achieve the trade-off between control performance and robustness [20][21][22]. L 1 adaptive control, an improvement of model reference adaptive control (MRAC) presented by Cao and Hovakimyan, appears to be beneficial both for robustness and performance [22][23][24], resolving the trade-off between the two by selecting a low-level filtering structure.…”
Section: Introductionmentioning
confidence: 99%
“…Falkiewicz et al [39] presented an analysis of how to include the aerothermoelastic effects into the simulation of a hypersonic vehicle. Moreover, Chen et al [40] studied the use of the L1 adaptive control for a model of the generic hypersonic vehicle.…”
Section: Introductionmentioning
confidence: 99%