Abstract
Section 4.2 details the problem formulation. In Sect. 4.3, the NN is used to approach the system uncertainties in the UAV attitude dynamics model. A DTDO based on the NN is also designed in Sect. 4.3, and the designed DTDO is used to estimate the external disturbance. Furthermore, according to the tracking differentiator with discrete-time form, the NN-based nonlinear DTDO and the BC technology, a discrete-time controller based on the NN is designed, and discrete-time Lyapunov stability theory is used to prove that the designed discrete-time controller can ensure the boundedness of closed-loop system signals in Sect. 4.3. The UAV attitude dynamic model with wind disturbance and system uncertainties is simulated and analyzed in Sect. 4.4, and the simulation results further illustrate the effectiveness of the proposed discrete-time flight control scheme, followed by drawing some conclusions in Sect. 4.5.
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References
Suresh, S., Kannan, N.: Direct adaptive neural flight control system for an unstable unmanned aircraft. Appl. Soft Comput. 8(2), 937–948 (2008)
Suresh, S., Omkar, S.N., Mani, V., et al.: Direct adaptive neural flight controller for F-8 fighter aircraft. J. Guid. Control Dyn. 29(2), 454–464 (2006)
Lee, T., Kim, Y.: Nonlinear adaptive flight control using backstepping and neural networks controller. J. Guid. Control Dyn. 24(4), 675–682 (2001)
Lei, X., Ge, S.S., Fang, J.: Adaptive neural network control of small unmanned aerial rotorcraft. J. Intell. Robot. Syst. 75(2), 331–341 (2014)
Zhang, C., Hu, H., Wang, J.: An adaptive neural network approach to the tracking control of micro aerial vehicles in constrained space. Int. J. Syst. Sci. 48(1), 84–94 (2017)
Bu, X., Wu, X., Wei, D., et al.: Neural-approximation-based robust adaptive control of flexible air-breathing hypersonic vehicles with parametric uncertainties and control input constraints. Inf. Sci. 346, 29–43 (2016)
Lei, X., Lu, P.: The adaptive radial basis function neural network for small rotary-wing unmanned aircraft. IEEE Trans. Ind. Electron. 61(9), 4808–4815 (2014)
Chen, W.-H.: Nonlinear disturbance observer-enhanced dynamic inversion control of missiles. J. Guid. Control Dyn. 26(1), 161–166 (2003)
Xu, B.: Disturbance observer-based dynamic surface control of transport aircraft with continuous heavy cargo airdrop. IEEE Trans. Syst. Man Cybern. Syst. 47(1), 161–170 (2017)
He, W., Yan, Z., Sun, C., et al.: Adaptive neural network control of a flapping wing micro aerial vehicle with disturbance observer. IEEE Trans. Cybern. 47(10), 3452–3465 (2017)
Chen, M., Ren, B., Wu, Q., et al.: Anti-disturbance control of hypersonic flight vehicles with input saturation using disturbance observer. Sci. China Inf. Sci. 58(7), 1–12 (2015)
Chen, F., Lei, W., Zhang, K., et al.: A novel nonlinear resilient control for a quadrotor uav via backstepping control and nonlinear disturbance observer. Nonlinear Dyn. 85(2), 1281–1295 (2016)
Besnard, L., Shtessel, Y.B., Landrum, B.: Quadrotor vehicle control via sliding mode controller driven by sliding mode disturbance observer. J. Frankl. Inst. 349(2), 658–684 (2012)
Lee, K., Back, J., Choy, I.: Nonlinear disturbance observer based robust attitude tracking controller for quadrotor UAVs. Int. J. Control Autom. Syst. 12(6), 1266–1275 (2014)
Wang, H., Chen, M.: Trajectory tracking control for an indoor quadrotor UAV based on the disturbance observer. Trans. Inst. Meas. Control 38(6), 675–692 (2016)
Yang, J., Li, S., Sun, C., et al.: Nonlinear-disturbance-observer-based robust flight control for airbreathing hypersonic vehicles. IEEE Trans. Aerosp. Electron. Syst. 49(2), 1263–1275 (2013)
Wu, G., Meng, X.: Nonlinear disturbance observer based robust backstepping control for a flexible air-breathing hypersonic vehicle. Aerosp. Sci. Technol. 54, 174–182 (2016)
Sun, H., Li, S., Yang, J., et al.: Non-linear disturbance observer-based back-stepping control for airbreathing hypersonic vehicles with mismatched disturbances. IET Control Theory Appl. 8(17), 1852–1865 (2014)
Chen, M., Yu, J.: Disturbance observer-based adaptive sliding mode control for near-space vehicles. Nonlinear Dyn. 82(4), 1671–1682 (2015)
Lu, H., Liu, C., Guo, L., et al.: Flight control design for small-scale helicopter using disturbance-observer-based backstepping. J. Guid. Control Dyn. 38(11), 2235–2240 (2015)
Han, Y., Li, P., Zheng, Z.: A non-decoupled backstepping control for fixed-wing UAVs with multivariable fixed-time sliding mode disturbance observer. In: Transactions of the Institute of Measurement and Control (2018). https://doi.org/10.1177/0142331218793178
Smith, J., Su, J., Liu, C., et al.: Disturbance observer based control with anti-windup applied to a small fixed wing UAV for disturbance rejection. J. Intell. Robot. Syst. 88(2–4), 329–346 (2017)
Osa, Y., Mabuchi, T., Uchikado, S.: Synthesis of discrete time adaptive flight control system using nonlinear model matching. IEEE Int. Symp. Ind. Electron. 1, 58–63 (2001)
Xiong, J.-J., Zhang, G.: Discrete-time sliding mode control for a quadrotor UAV. Optik 127(8), 3718–3722 (2016)
Jiang, B., Chowdhury, F.N.: Fault estimation and accommodation for linear MIMO discrete-time systems. IEEE Trans. Control Syst. Technol. 13(3), 493–499 (2005)
Xu, B., Sun, F., Yang, C., et al.: Adaptive discrete-time controller design with neural network for hypersonic flight vehicle via back-stepping. Int. J. Control 84(9), 1543–1552 (2011)
Xu, B., Wang, D., Sun, F., et al.: Direct neural discrete control of hypersonic flight vehicle. Nonlinear Dyn. 70(1), 269–278 (2012)
Xu, B., Zhang, Y.: Neural discrete back-stepping control of hypersonic flight vehicle with equivalent prediction model. Neurocomputing 154, 337–346 (2015)
Shin, D.-H., Kim, Y.: Nonlinear discrete-time reconfigurable flight control law using neural networks. IEEE Trans. Control Syst. Technol. 14(3), 408–422 (2006)
Mareels, I.M., Penfold, H., Evans, R.J.: Controlling nonlinear time-varying systems via euler approximations. Automatica 28(4), 681–696 (1992)
Yan, X., Chen, M., Feng, G. et al.: Fuzzy robust constrained control for nonlinear systems with input saturation and external disturbances. In: IEEE Transactions on Fuzzy Systems (2019). https://doi.org/10.1109/TFUZZ.2019.2952794
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Shao, S., Chen, M., Shi, P. (2021). Discrete-Time Adaptive NN Tracking Control of an Uncertain UAV System Based on DTDO. In: Robust Discrete-Time Flight Control of UAV with External Disturbances. Studies in Systems, Decision and Control, vol 317. Springer, Cham. https://doi.org/10.1007/978-3-030-57957-9_4
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