Synthesis of intelligent control algorithms for a class of naval aerial vehicles
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https://doi.org/10.54939/1859-1043.j.mst.97.2024.50-58Keywords:
Autonomous Aerial Vehicles; Missile; UAV; Neural network.Abstract
Autonomous aerial vehicles in the Navy are modern aircraft widely used in military applications. Current techniques are primarily based on linear control theory, which may overlook nonlinear elements in the model or external disturbances in the operational environment. Therefore, this paper presents a method for synthesizing adaptive fuzzy neural network control algorithms for a class of autonomous aerial vehicles in the Navy to stabilize desired characteristic angles. The study is conducted in a Matlab/Simulink environment with assumed parameters, and comparisons are made with a PID controller to demonstrate the advantages of the proposed algorithm.
References
[1]. Phạm Quang Hiếu, “Synthesis of control systems for variable-speed flying devices”, Doctoral dissertation, Institute of Science and Technology, Hanoi, (2018).
[2]. P. Quang Hieu; T. Tuan Don. “Synthesizing an Adaptive Control Law for a Class of Autonomous Aerial Vehicles in the Navy”, In: International Conference on Advanced Mechanical Engineering, Automation and Sustainable Development. Cham: Springer International Publishing, pp. 765-769, (2021). DOI: https://doi.org/10.1007/978-3-030-99666-6_110
[3]. M. Fawzy, M. A. S. Aboelela, O. Abd El Rhman, H. T. Dorrah, “Design of Missile Control System Using Model Predictive Control”, The Online Journal on Computer Science and Information Technology, Vol.1(3), 64-70, (2011).
[4]. W.Y.Wang, Y.G.Leu, T.T.Lee, “Output Feedback Control of Nonlinear Systems Using Direct Adaptive Fuzzy – Neural Controller” Fuzzy Set and Systems, pp 341-358, (2002). DOI: https://doi.org/10.1016/S0165-0114(02)00519-5
[5]. T. T. Don, N. Q. Hung, N. Q. Vinh, N. D. Anh, T. V. Nhan and N. M. Tu, “Synthesis of Optimal Control Law for Nonlinear Systems Based on Integration of Artificial Neural Network and LQR Controller,” 2023 12th International Conference on Control, Automation and Information Sciences (ICCAIS), Hanoi, Vietnam, pp. 612-616, (2023), doi: 10.1109/ICCAIS59597.2023.10382283. DOI: https://doi.org/10.1109/ICCAIS59597.2023.10382283
[6]. L. X. Wang, “Adaptive Fuzzy Systems and Control: Design and Stability Analysis”. Englewood Cliffs, NJ: Prentice-Hall, (1994).
[7]. W. Gao and R. R. Selmic, “Neural network control of a class of nonlinear systems with actuator saturation”, IEEE Trans. Neural Netw., Vol. 17, No. 1. pp. 147 – 156, (2006). DOI: https://doi.org/10.1109/TNN.2005.863416
[8]. H. K. Lam and F. H. F. Leung, “Fuzzy controller with stability and performance rules for nonlinear systems”, Fuzzy Sets Syst., Vol. 158, No. 2. pp. 147–163, (2007). DOI: https://doi.org/10.1016/j.fss.2006.06.005
[9]. Cliton E.Plaisted, “Design of an adaptive autopilot for an expendable launch vehicle”. University of Central Florida, Florida, (2008).
[10]. Nguyễn Duy Hưng, “Về một phương pháp tổng hợp hệ điều khiển mờ dùng mạng nơ ron ứng dụng trong công nghiệp”, Luận án Tiến sĩ kỹ thuật, Hà nội, (2009).
[11]. Nguyễn Văn Chung, Đỗ Như Ý, Phạm Quang Hiếu, “Khảo sát nguyên lý điều khiển kết hợp của tên lửa không đối không”, Tuyển tập Công trình khoa học Hội nghị Cơ điện tử toàn quốc lần thứ 8, NXB Khoa học Tự nhiên và Công Nghệ, Hà Nội, tr.131-134, (2016).
