Modern new tanks are difficult to achieve high precision control of the horizontal stabilization system due to electromechanical coupling and road surface disturbance during high-speed combat. A predefined-time dynamic surface controller (DSCPT) is proposed for the fast stabilization and strong disturbance problems of the tank horizontal stabilization system. Based on backstepping control technique, the controller introduces a time-varying tuning function and a first-order filter to construct the dynamic surface error, where the time-varying tuning function ensures that the tracking error is bounded within a predefined time, and the hyperbolic tangent function ensures robustness and the continuity of the control input. Using Lyapunov theory, it is rigorously demonstrated that the control method is capable of achieving tracking error convergence to a predetermined range at any predefined time in the presence of system uncertainty, and that it is able to ensure global stabilization of the closed-loop system. In addition, a transfer model is used to link pavement roughness and major disturbance, and then added to the simulation. Finally, the effectiveness of the proposed control method is verified through a large number of comparative simulations.
| [1] |
Y. Ma, G. Yang, Q. Sun, X. Wang, and Z. Wang, “Adaptive Robust Feedback Control of Moving Target Tracking for All-Electrical Tank With Uncertainty,” Defence Technology 18, no. 4 (2022): 626–642.
|
| [2] |
S. S. Yuan, W. X. Deng, J. Y. Yao, and G. L. Yang, “Robust Adaptive Precision Motion Control of Tank Horizontal Stabilizer Based on Unknown Actuator Backlash Compensation,” Defence Technology 20 (2023): 72–83.
|
| [3] |
S. Yuan, W. Deng, J. Yao, and G. Yang, “Nonlinear Robust Adaptive Control for Bidirectional Stabilization System of All-Electric Tank With Unknown Actuator Backlash Compensation and Disturbance Estimation,” Defence Technology 32 (2024): 144–158.
|
| [4] |
Y. Zhang, Y. X. Zhang, and Y. Chen, “Artillery Servo System Based on Fuzzy-Pid Control,” Science Technology and Engineering 12, no. 19 (2012): 4630–4633.
|
| [5] |
Q. Gao, J. Chen, L. Wang, S. Xu, and Y. Hou, “Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System,” Scientific World Journal 2013, no. 1 (2013): 907256.
|
| [6] |
A. G. Alexandrov and M. V. Palenov, “Adaptive PID Controllers: State of the Art and Development Prospects,” Automation and Remote Control 75 (2014): 188–199.
|
| [7] |
N. D. Phu, N. N. Hung, A. Ahmadian, and N. Senu, “A New Fuzzy PID Control System Based on Fuzzy PID Controller and Fuzzy Control Process,” International Journal of Fuzzy Systems 22, no. 7 (2020): 2163–2187.
|
| [8] |
C. T. Chao, N. Sutarna, J. S. Chiou, and C. J. Wang, “An Optimal Fuzzy PID Controller Design Based on Conventional PID Control and Nonlinear Factors,” Applied Sciences 9, no. 6 (2019): 1224.
|
| [9] |
L. J. Shen, Y. Bao, and J. P. Cai, “Adaptive Control of Uncertain Gun Control System of Tank,” Applied Mechanics and Materials 88–89 (2011): 88–92.
|
| [10] |
Y. Chen and G. Yang, “Dynamic Simulation of Tank Stabilizer Based on Adaptive Control,” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 9 (2019): 3038–3049.
|
| [11] |
S. Yuan, W. Deng, Y. Ge, J. Yao, and G. Yang, “Nonlinear Adaptive Robust Precision Pointing Control of Tank Servo Systems,” IEEE Access 9 (2021): 23385–23397.
|
| [12] |
Y. Chen, G. Yang, and Q. Sun, “Dynamic Simulation on Vibration Control of Marching Tank Gun Based on Adaptive Robust Control,” Journal of Low Frequency Noise, Vibration and Active Control 39, no. 2 (2020): 416–434.
|
| [13] |
Y. Ma, G. Yang, Q. Sun, X. Wang, and Q. Sun, “Adaptive Robust Control for Tank Stability: A Constraint-Following Approach,” Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 235, no. 1 (2021): 3–14.
|
| [14] |
D. Lin, X. Wang, G. Yang, S. Yuan, and Q. Sun, “Adaptive Robust Control for Fully Electric Pitch System of Tank With Dynamic Friction Compensation,” Journal of Mechanical Science and Technology 36, no. 10 (2022): 4967–4978.
|
| [15] |
D. Lin, X. Wang, Y. Wang, and G. Yang, “Adaptive Robust Servo Control for Vertical Electric Stabilization System of Tank and Experimental Validation,” Defence Technology 31 (2024): 326–342.
|
| [16] |
X. Ma, W. X. Deng, S. S. Yuan, J. Y. Yao, and G. L. Yang, “Neural Network Based Adaptive Rise Control of Tank Gun Systems,” Journal of Physics: Conference Series 1507, no. 5 (2020): 052001.
|
| [17] |
C. Wang, S. Yuan, and J. Yao, “ESO-Based Active Stability Control of Tank Guns on the Move With Uncertainties,” 2021 China Automation Congress (CAC), IEEE (2021): 1358–1363.
|
| [18] |
H. Zheng, X. Rui, J. Zhang, S. Zhang, and J. Gu, “Improved Modeling and Active Disturbance Rejection Control of Tank Gun Control System,” Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 236, no. 9 (2022): 1649–1666.
|
| [19] |
Y. Xia, L. Dai, M. Fu, C. Li, and C. Wang, “Application of Active Disturbance Rejection Control in Tank Gun Control System,” Journal of the Franklin Institute 351, no. 4 (2014): 2299–2314.
|
| [20] |
Y. Xia, F. Pu, M. Fu, and L. Ye, “Modeling and Compound Control for Unmanned Turret System With Coupling,” IEEE Transactions on Industrial Electronics 63, no. 9 (2016): 5794–5803.
|
| [21] |
W. Zhao, Y. Xia, H. Song, Z. Sun, and Y. Xu, “Application of Active Disturbance Rejection Control in Tank Gun Control System,” 2021 40th Chinese Control Conference (CCC), IEEE (2021): 2051-2056.
|
| [22] |
S. Yuan, J. Yao, W. Deng, G. Yang, and X. Ma, “Active Disturbance Rejection Adaptive Control of Tank Turret-Gun Control Systems,” 2020 39th Chinese Control Conference (CCC), IEEE (2020): 333–339.
|
| [23] |
J. Yao and W. Deng, “Active Disturbance Rejection Adaptive Control of Hydraulic Servo Systems,” IEEE Transactions on Industrial Electronics 64, no. 10 (2017): 8023–8032.
|
| [24] |
K. Liu, Y. Wu, T. Zhu, Y. Chen, Y. Lu, and D. Zhao, “Improved RBF Network Torque Control in Flexible Manipulator Actuated by PMAs,” Robotica 37, no. 2 (2019): 264–280.
|
| [25] |
J. Liu, Radial Basis Function (RBF) Neural Network Control for Mechanical Systems: Design, Analysis and Matlab Simulation (Springer Science & Business Media, 2013), 55.
|
| [26] |
J. Zhang, D. Chen, G. Shen, Z. Sun, and Y. Xia, “Disturbance Observer Based Adaptive Fuzzy Sliding Mode Control: A Dynamic Sliding Surface Approach,” Automatica 129 (2021): 109606.
|
| [27] |
J. Li, Z. Zhang, X. Gao, P. Wang, and J. Li, “Relation Between Power Spectral Density of Road Roughness and International Roughness Index and Its Application,” International Journal of Vehicle Design 77, no. 4 (2018): 247–271.
|
RIGHTS & PERMISSIONS
2025 The Author(s). International Journal of Mechanical System Dynamics published by John Wiley & Sons Australia, Ltd on behalf of Nanjing University of Science and Technology.
PDF
(1579KB)
