An adaptive anti-swing control for the helicopter slung-load system based on trajectory planning and neural network. (English) Zbl 1537.93520
Summary: In this article, an adaptive anti-swing control method based on trajectory planning and radial basis function neural network (RBFNN) is proposed for the unmanned helicopter slung-load system with the external disturbances and the continuous system uncertainty. An online trajectory planning method is designed to obtain the desired position, velocity, and acceleration signals of the unmanned helicopter. Then, combining with RBFNN and sliding mode control method, the position loop controller of the unmanned helicopter is designed to make the swing angle stable, and the unmanned helicopter can also track the desired trajectory. The attitude loop controller is designed by sliding mode backstepping method and RBFNN. In the process of controller design, the adaptive laws are designed to adjust the influence of approximation error of RBFNN and the external disturbance. The stability of the closed-loop system is proved by Lyapunov analysis. Numerical simulation results show that the proposed control strategy is effective.
{© 2022 John Wiley & Sons Ltd.}
{© 2022 John Wiley & Sons Ltd.}
MSC:
| 93C85 | Automated systems (robots, etc.) in control theory |
| 70Q05 | Control of mechanical systems |
| 93C40 | Adaptive control/observation systems |
Keywords:
adaptive control; neural network; sliding mode control; slung-load; trajectory planning; unmanned helicopterReferences:
| [1] | CaoYH, WangZR. Equilibrium characteristics and stability analysis of helicopter slung‐load system. Proc Inst Mech Eng G J Aerosp Eng. 2017;231(G6):1056‐1064. |
| [2] | WangF, LiuP, ZhaoS, et al. Guidance, navigation and control of an unmanned helicopter for automatic cargo transportation. Proceedings of the 33rd Chinese Control Conference; 2014:1013‐1020. |
| [3] | CourharboAL, BisgaardM. State‐control trajectory generation for helicopter slung load system using optimal control. Proceedings of the AIAA Guidance, Navigation, and Control Conference; 2009:1‐16. |
| [4] | OktayT, SultanC. Modeling and vontrol of a helicopter slung‐load system. Aerosp Sci Technol. 2013;29(1):206‐222. |
| [5] | El‐FerikS, Syed AsimH, Omar HanafyM, DericheMA. Nonlinear forward path tracking controller for helicopter with slung load. Aerosp Sci Technol. 2017;69:602‐608. |
| [6] | BisgaardM, Cour‐HarboAL, BendtsenJ. Input shaping for helicopter slung load swing reduction. Proceed AIAA Guidance, Navigation and Control Conference and Exhibit; 2008. |
| [7] | RenY, LiK, YeH. Modeling and anti‐swing control for a helicopter slung‐load system. Appl Math Comput. 2020;372:1‐17. · Zbl 1433.93092 |
| [8] | LinX, YuY, SunCY. A decoupling control for quadrotor UAV using dynamic surface control and sliding mode disturbance observer. Nonlinear Dyn. 2019;97(1):781‐795. |
| [9] | WuKJ, ZhangPX, WuH. A new control design for a morphing UAV based on disturbance observer and command filtered backstepping techniques. Sci China Technol Sci. 2019;62(10):1845‐1853. |
| [10] | XianB, GuoJ, YaoZ, BoZ. Sliding mode tracking control for miniature unmanned helicopters. Chin J Aeronaut. 2015;28(1):277‐284. |
| [11] | GaoY, FuJ, ChenW, WuQ. Chattering‐free sliding mode control with unidirectional auxiliary surfaces for miniature helicopters. Int J Intell Comput Cybern. 2012;5(3):421‐438. |
| [12] | FangX, WuA, ShangY, DongN. A novel sliding mode controller for small‐scale unmanned helicopters with mismatched disturbance. Nonlinear Dyn. 2016;23:1053‐1068. · Zbl 1349.93282 |
| [13] | FangX, ShangY. Trajectory tracking control for small‐scale unmanned helicopters with mismatched disturbances based on a continuous sliding mode approach. Int J Aerosp Eng. 2019;2019(PT.2):6235862.1‐6235862.15. |
| [14] | CaiL, ChenFY, LuFF. Global robust sliding mode tracking control for helicopter with input time delay. Adv Mater Res. 2014;846:434‐437. |
| [15] | WanM, ChenM, YanK. Adaptive sliding mode tracking control for unmanned autonomous helicopters based on neural networks. Complexity. 2018;15:1‐11. · Zbl 1407.93182 |
| [16] | LiuL, ChenM, LiT, WangH. Composite anti‐disturbance reference model \(\operatorname{L}_2 - \operatorname{L}_{\operatorname{\infty}}\) control for helicopter slung load system. J Intell Robot Syst. 2021;102(1):1‐21. |
| [17] | LuB, WuZ, FangYC, SunN. Input shaping control for two crane systems with holonomic constraints. Control Theory Appl. 2018;35(12):1805‐1811. |
| [18] | MaghsoudiMJ, LiyanaR, SudinS, MohamedZ, WahidH. Improved unity magnitude input shaping scheme for sway control of an underactuated 3D overhead crane with hoisting. Mech Syst Signal Process. 2019;123:466‐482. |
| [19] | HuG, MakkarC, DixonWE. Energy‐based nonlinear control of underactuated Euler‐Lagrange systems subject to impacts. IEEE Trans Automat Contr. 2007;52(9):1742‐1748. · Zbl 1366.93438 |
| [20] | EnL, Zi‐ZeL, Zeng‐GuangH, MinT. Energy‐based balance control approach to the ball and beam system. Int J Control. 2009;82(6):981‐992. · Zbl 1168.93398 |
| [21] | LiuJK. Sliding Mode Control Design and MATLAB Simulation of the Design Method of Advanced Control System. Tsinghua University Press; 2015. |
| [22] | YanK, WuQ, ChenM. Robust adaptive backstepping control for unmanned autonomous helicopter with flapping dynamics. Proceedings of the 2017 13th IEEE International Conference on Control Automation (ICCA); 2017:1027‐1032. |
| [23] | LiangX, FangY, SunN, LinH. Nonlinear hierarchical control for unmanned quadrotor transportation systems. IEEE Trans Ind Electron. 2018;65(4):3395‐3405. |
| [24] | YuG, CabecinhasD, CunhaR, SilvestreC. Nonlinear backstepping control of a quadrotor slung‐load system. IEEE/ASME Trans Mechatron. 2019;24(5):2304‐2315. |
| [25] | SunN, FangY, ZhangY, MaB. A novel kinematic voupling‐based trajectory planning method for overhead cranes. IEEE/ASME Trans Mechatron. 2012;17(1):166‐173. |
| [26] | SunN, FangY. An efficient online trajectory generating method for underactuated crane systems. Int J Robust and Nonlinear Control. 2014;24(11):1653‐1663. · Zbl 1298.93243 |
| [27] | XianB, WangS, YangS. An online trajectory planning approach for a quadrotor UAV with a slung payload. IEEE Trans Ind Electron. 2020;67(8):6669‐6678. |
| [28] | LeeCT, TsaiCC. Improved nonlinear trajectory tracking using RBFNN for a robotic helicopter. Int J Robust Nonlinear Control. 2010;20(10):1079‐1096. · Zbl 1200.93106 |
| [29] | ChenM, GeSS. Direct adaptive neural control for a class of uncertain nonaffine nonlinear systems based on disturbance observer. IEEE Trans Cybern. 2013;43(4):1213‐1225. |
| [30] | RoyS, RoySB, KarIN. Adaptive-robust control of Euler-Lagrange systems with linearly parametrizable uncertainty bound. IEEE Trans Control Syst Technol. 2018;26(5):1842‐1850. |
| [31] | FangX, WuAG, DongN. Adaptive backstepping‐based trajectory control of an unmanned helicopter in presence of wind gusts. J Chinese Inertial Technol. 2015;23(1):59‐65. |
| [32] | ChenM, TaoG, JiangB. Dynamic surface control using neural networks for a class of uncertain nonlinear systems with input saturation. IEEE Trans Neural Netw Learn Syst. 2015;26(9):2086‐2097. |
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.
