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Terminal Guidance Law for UAV Based on Receding Horizon Control Strategy

Author

Listed:
  • Zhenglong Wu
  • Zhenyu Guan
  • Chengwei Yang
  • Jie Li

Abstract

Terminal guidance law against the maneuvering target is always the focal point. Most of the literatures focus on estimating the acceleration of target and time to go in guidance law, which are difficult to acquire. This paper presents a terminal guidance law based on receding horizon control strategy. The proposed guidance law adopts the basic framework of receding horizon control, and the guidance process is divided into several finite time horizons. Then, optimal control theory and target motion prediction model are used to derive guidance law for minimum time index function with continuous renewal of original conditions at the initial time of each horizon. Finally, guidance law performs repeated iteration until intercepting the target. The guidance law is of subprime optimal type, requiring less guidance information, and does not need to estimate the acceleration of target and time to go. Numerical simulation has verified that the proposed guidance law is more effective than traditional methods on constant and sinusoidal target with bounded acceleration.

Suggested Citation

  • Zhenglong Wu & Zhenyu Guan & Chengwei Yang & Jie Li, 2017. "Terminal Guidance Law for UAV Based on Receding Horizon Control Strategy," Complexity, Hindawi, vol. 2017, pages 1-19, May.
  • Handle: RePEc:hin:complx:2750172
    DOI: 10.1155/2017/2750172
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    Cited by:

    1. Jesús Enrique Sierra & Matilde Santos, 2019. "Wind and Payload Disturbance Rejection Control Based on Adaptive Neural Estimators: Application on Quadrotors," Complexity, Hindawi, vol. 2019, pages 1-20, January.
    2. Mao Su & Lei Liu & Yongji Wang, 2018. "Integrated Estimation/Guidance Law against Exoatmospheric Maneuvering Targets," Complexity, Hindawi, vol. 2018, pages 1-19, December.
    3. Víctor San Juan & Matilde Santos & José Manuel Andújar, 2018. "Intelligent UAV Map Generation and Discrete Path Planning for Search and Rescue Operations," Complexity, Hindawi, vol. 2018, pages 1-17, April.

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