The purpose of this paper is to develop the control system using the Elman neural network (ENN) and nonsingular terminal sliding mode control (NTSMC) to improve the automatic landing capability of carrier-based aircraft based on direct lift control (DLC) when subjected to carrier air-wake disturbance and actuator failure. First, the carrier-based aircraft landing model is derived. Then, the NTSMC is proposed to ensure the system’s robustness and achieve accurate trajectory tracking performance in a finite time. Due to the inclusion of nonsingularity in NTSMC, the steady-state response of the control system can be effectively improved. In addition, the ENN is derived using an adaptive learning algorithm to approximate the actuator faults and system uncertainties. To further ensure the accurate tracking of the ideal glide path by the carrier-based aircraft, the NTSMC system using an ENN estimator is proposed. Finally, this method is tested by adding different types of actuator failures. The simulation results show that the designed longitudinal fault-tolerant carrier landing system has strong robustness and fault-tolerant ability and improves the accuracy of carrier-based aircraft landing trajectory tracking.


    Access

    Download


    Export, share and cite



    Title :

    Elman Neural Network-Based Direct Lift Automatic Carrier Landing Nonsingular Terminal Sliding Mode Fault-Tolerant Control System Design


    Contributors:
    Qilong Wu (author) / Qidan Zhu (author) / Shuai Han (author)


    Publication date :

    2023




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown





    Nonsingular and Fast Terminal Sliding Mode Control Method

    Li, S.-b. / Li, K.-q. / Wang, J.-q. et al. | British Library Online Contents | 2009



    Fast nonsingular terminal sliding mode control based on multi-slide-mode

    Xia, Z. / Yuxian, J. / Yunjie, W. et al. | British Library Online Contents | 2011


    Fault-Tolerant Robust Automatic Landing Control Design

    Fang Liao / Jian Liang Wang / Eng Kee Poh et al. | AIAA | 2005