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Intelligent control system design for UAV using a recurrent wavelet neural network

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Abstract

This paper aims to propose an efficient control algorithm for the unmanned aerial vehicle (UAV) motion control. An intelligent control system is proposed by using a recurrent wavelet neural network (RWNN). The developed RWNN is used to mimic an ideal controller. Moreover, based on sliding-mode approach, the adaptive tuning laws of RWNN can be derived. Then, the developed RWNN control system is applied to an UAV motion control for achieving desired trajectory tracking. From the simulation results, the control scheme has been shown to achieve favorable control performance for the UAV motion control even it is subjected to control effort deterioration and crosswind disturbance.

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Authors and Affiliations

  1. Department of Electrical Engineering, Yuan Ze University, Chung-Li, Tao-Yuan, 320, Taiwan, ROC

    Chih-Min Lin, Ching-Fu Tai & Chang-Chih Chung

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  1. Chih-Min Lin
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  2. Ching-Fu Tai
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  3. Chang-Chih Chung
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Correspondence to Chih-Min Lin.

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Lin, CM., Tai, CF. & Chung, CC. Intelligent control system design for UAV using a recurrent wavelet neural network. Neural Comput & Applic 24, 487–496 (2014). https://doi.org/10.1007/s00521-012-1242-5

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  • DOI: https://doi.org/10.1007/s00521-012-1242-5

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