Synthesis of Adaptive Neuro-Fuzzy Control Algorithmsfor a Class of Autonomous Aerial Vehicles

Authors

  • Tran Tuan Don Academy of Military Science and Technology, Ha Noi, Viet Nam
  • Nguyen Quang Vinh Academy of Military Science and Technology, Ha Noi, Viet Nam
  • Nguyen Quang Hung East Asia University of Technology (EAUT), Ha Noi, Viet Nam
  • Pham Quang Hieu Missile - ship artillery department, Naval Academy, Khanh Hoa, Vietnam
  • Nguyen Tat Tuan Le Quy Don Technical University, Hanoi, Vietnam

DOI:

https://doi.org/10.3849/aimt.01906

Keywords:

neural network, fuzzy control, adaptive control. , missile

Abstract

Autonomous flying devices (AFDs) in the Navy are modern flying devices widely used in the military sector as the flying device changes speed and altitude, its kinematic characteristics vary significantly, requiring a controller capable of adapting to these changes. Therefore, this paper presents a method for synthesizing an adaptive fuzzy neural network control algorithm for autonomous naval flying devices to stabilize the desired characteristic angles. A Matlab/Simulink environment survey is conducted with assumed parameters and the results are compared with those of a PID controller to highlight the advantages of the proposed algorithm.

References

PLAISTED, C.E. Design of an Adaptive Autopilot for an Expendable Launch Vehicle [online]. [Master Thesis]. Orlando: University of Central Florida, 2008 [viewed 2024-03-21]. Available from: https://core.ac.uk/download/pdf/236295986.pdf

FAWZY, M., M.A.S. ABOELELA, O. ABD EL RHMAN and H.T. DORRAH. Design of Missile Control System Using Model Predictive Control. The Online Journal on Computer Science and Information Technology, 2011, 1(3), pp. 64–70.

TURKOGLU, K., U. OZDEMIR, M. NIKBAY and E.M. JAFAROV. PID Parameter Optimization of an UAV Longitudinal Flight Control System. International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering, 2008, 2(9), pp. 35–40. https://doi.org/10.5281/zenodo.1079352

TONG, S., T. WANG and J.T. TANG. Fuzzy Adaptive Output Tracking Control of Nonlinear System. Fuzzy Sets and Systems, 2000, 111(2), pp. 1169–1182. https://doi.org/10.1016/S0165-0114(98)00058-X

WANG, L.-X. Adaptive Fuzzy Systems and Control, Design and Stability Analysis. Hoboken: PTR Prentice Hall, 1994. ISBN 0-13-099631-9

ROVITHAKIS, C.A. and M.A. CHRISTODOULOU. Adaptive Control of Unknown Plans Using Dynamical Neural Network. IEEE Transactions on Systems, Man, and Cybernetics, 1995, 24(3), pp. 400–412. https://doi.org/10.1109/21.278990

GE, S.S., C.C. HANG, T.H. LEE and T. ZHANG. Stable Adaptive Neural Network Control. New York: Springer, 2001. ISBN 1-4419-4932-1

ZHANG, T., S.S. GE and C.C. HANG. Adaptive Output Feedback Control for General Nonlinear Systems Using Multilayer Neural Networks. In: Proceedings of the 1998 American Control Conference. Philadelphia: IEEE, 1998. https://doi.org/10.1109/ACC.1998.694722

HORIKAWA, S., T. FURUHASHI and Y. UCHIKAWA. On Fuzzy Modeling Using Fuzzy Neural Networks with the Back-Propagation Algorithm. IEEE Transactions on Neural Networks, 1992, 3(5), pp. 801–806. https://doi.org/10.1109/72.159069

WANG, W.Y., Y.G. LEU and C.C. HSU. Robust Adaptive Fuzzy-Neural Control of Nonlinear Dynamical Systems Using Generalized Projection Update Law and Variable Structure Controller. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2001, 31(1), pp. 140–147. https://doi.org/10.1109/3477.907573

PHAM, Q.H. and T.D. TRAN. Synthesizing an Adaptive Control Law for a Class of Autonomous Aerial Vehicles in the Navy. In: Proceedings of the International Conference on Advanced Mechanical Engineering, Automation, and Sustainable Development 2021 (AMAS2021). Cham: Springer, 2021, pp. 765–769. https://doi.org/10.1007/978-3-030-99666-6_110

SIOURIS, G.M. Missile Guidance and Control Systems. New York: Springer, 2004. ISBN 0-387-00726-1

LABIOD, S., M.S. BOUCHERIT and T.M. GUERRA. Adaptive Fuzzy Control of a Class of MIMO Nonlinear Systems. Fuzzy Set and Systems, 2005, 151(1), pp. 59–77. https://doi.org/10.1016/j.fss.2004.10.009

IOANNOU, P.A. and J. SUN. Robust Adaptive Control [online]. Hoboken: Prentice–Hall, 1996 [viewed 2024-03-24]. Available from: https://viterbi-web.usc.edu/~ioannou/RobustAdaptiveBook95pdf/Robust_Adaptive_Control.pdf

WANG, W.-Y., Y.-G. LEU and T.-T. LEE. Output – Feedback Control of Nonlinear Systems Using Direct Adaptive Fuzzy – Neural Controller. Fuzzy Set and Systems, 2002, 140(2), pp. 341–358. https://doi.org/10.1016/S0165-0114(02)00519-5

LANDAU, I.D., R. LOZANO, M. MSAAD and A. KARIMI. Adaptive Control – Algorithms, Analysis and Applications. London: Springer, 2011. ISBN 0-85729-663-9

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Published

13-06-2025

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Section

Original research article

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How to Cite

Tran Tuan, D., Nguyen Quang, V., Nguyen Quang, H., Pham Quang, . H., & Nguyen Tat, T. (2025). Synthesis of Adaptive Neuro-Fuzzy Control Algorithmsfor a Class of Autonomous Aerial Vehicles. Advances in Military Technology, 20(1), 297-313. https://doi.org/10.3849/aimt.01906

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