Điều khiển trượt bền vững dựa trên chế độ Quasi mới và bộ quan sát mạng nơ-ron nhân tạo thích ứng cho robot
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Từ khóa
#Robot; RBF neural network; Observer; Adaptive; Sliding mode control.Tài liệu tham khảo
[1]. P. Bhavagna Sai Rajeev et al., “Dynamic analysis of single link and R-P manipulators”, International Journal of Science, Technology and Management (IJSTM), vol. 11, no. 10, pp. 30–39, (2022).
[2]. T. S. Lee, E. A. Alandoli, “A critical review of modelling methods for flexible and rigid link manipulators”, Journal of the Brazilian Society of Mechanical Sciences and Engineering, vol. 42, no. 10, pp. 1–14, (2020).
[3]. K. Bingi, B. Rajanarayan Prusty, A. Pal Singh, “A review on fractional-order modelling and control of robotic manipulators”, Fractal and Fractional, vol. 7, no. 1, pp. 1–29, (2023).
[4]. J. Humaidi, I. K. Ibraheem, A. T. Azar, M. E. Sadiq, “A new adaptive synergetic control design for single link robot arm actuated by pneumatic muscles”, Entropy, vol. 22, no. 7, pp. 1–24, (2020).
[5]. Z. Yan, X. Lai, Q. Meng, P. Zhang, M. Wu, “Tracking control of single-link flexible-joint manipulator with unmodeled dynamics and dead zone”, International Journal of Robust and Nonlinear Control, vol. 31, no. 4, pp. 1270–1287, (2021).
[6]. A. Fayazi, N. Pariz, A. Karimpour, V. Feliu-Batlle, S. H. HosseinNia, “Adaptive sliding mode impedance control of single-link flexible manipulators interacting with the environment at an unknown intermediate point”, Robotica, vol. 38, no. 9, pp. 1642–1664, (2020).
[7]. Duong Xuan, “Dynamics and control analysis of a single flexible link robot with translational joints”, Science and Technology Development Journal – Engineering and Technology, vol. 3, no. 4, pp. 588–595, (2020).
[8]. Johnson Antony A., “Motion control of single link flexible joint robot manipulator using ANFIS MATLAB simulation”, Middle East Journal of Applied Science and Technology (MEJAST), vol. 2, no. 4, pp. 26–35, (2019).
[9]. D. Dermawan, H. Abbas, R. Syam, Z. Djafar, A. K. Muhammad, “Dynamic modeling of a single-link flexible manipulator robot with translational and rotational motions”, IIUM Engineering Journal, vol. 21, no. 1, pp. 228–239, (2020).
[10]. E. M. Raju, L. S. R. Krishna, Y. S. C. Mouli, V. N. Rao, “Effect of link flexibility on tip position of a single link robotic arm”, Journal of Physics: Conference Series, vol. 662, pp. 1–7, (2015).
[11]. A. Zhang, Z. Lin, B. Wang, Z. Han, “Nonlinear model predictive control of single-link flexible-joint robot using recurrent neural network and differential evolution optimization”, Electronics, vol. 10, no. 19, pp. 1–19, (2021).
[12]. J. F. Peza-Solís, G. Silva-Navarro, N. R. Castro-Linares, “Trajectory tracking control in a single flexible-link robot using finite differences and sliding modes”, Journal of Applied Research and Technology, vol. 13, no. 1, pp. 70–78, (2015).
[13]. H. Ullah, et al., “Robust output feedback control of single-link flexible-joint robot manipulator with matched disturbances using high gain observer”, Sensors, vol. 21, no. 9, pp. 1–22, (2021).
[14]. H. Zhang et al., “Radial basis function neural network sliding mode control for ship path following based on position prediction”, Journal of Marine Science and Engineering, vol. 9, p. 1055, (2021).
[15]. M. Mancini, E. Capello, E. Punta, “Sliding mode control with chattering attenuation and hardware constraints in spacecraft applications”, IFAC PapersOnLine, vol. 53, no. 2, pp. 5147–5152, (2020).
[16]. W. Alqaisi, C. El-Bayeh, “Adaptive control based on radial basis function neural network approximation for quadrotor”, Proceedings of the Annual System of Systems Engineering Conference (SOSE), pp. 214–219, (2022).
[17]. Y. H. Kim, F. L. Lewis, C. T. Abdallah, “A dynamic recurrent neural-network-based adaptive observer for a class of nonlinear systems”, Automatica, vol. 33, no. 8, pp. 1539–1543, (1997).
[18]. J. Liu, “Radial basis function (RBF) neural network control for mechanical systems: design, analysis and MATLAB simulation”, Springer, (2013).