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Composite dynamic surface control of hypersonic flight dynamics using neural networks

  • Research Paper
  • Special Focus on Advanced Nonlinear Control of Hypersonic Flight Vehicles
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Abstract

This paper addresses the composite neural tracking control for the longitudinal dynamics of hypersonicflight dynamics. The dynamics is decoupled into velocity subsystem, altitude subsystem, and attitudesubsystem. For the altitude subsystem, the reference command of flight path angle is derived for the attitudesubsystem. To deal with the system uncertainty and provide efficient neural learning, the composite law forneural weights updating is studied with both tracking error and modeling error. The uniformly ultimate boundednessstability is guaranteed via Lyapunov approach. Under the dynamic surface control with novel neuraldesign, the neural system converges in a faster mode and better tracking performance is obtained. Simulationresults are presented to show the effectiveness of the design.

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Authors and Affiliations

  1. Department of Automation, Tsinghua University, Beijing, 100084, China

    ShangMin Zhang & ChunWen Li

  2. Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China

    JiHong Zhu

Authors
  1. ShangMin Zhang
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  2. ChunWen Li
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  3. JiHong Zhu
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Correspondence to ShangMin Zhang.

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Zhang, S., Li, C. & Zhu, J. Composite dynamic surface control of hypersonic flight dynamics using neural networks. Sci. China Inf. Sci. 58, 1–9 (2015). https://doi.org/10.1007/s11432-015-5328-4

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  • DOI: https://doi.org/10.1007/s11432-015-5328-4

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