Trajectory Tracking Control Method of a Work-class ROV Based on a Super-twisting Second-order Sliding Mode Controller
-
摘要: 作业型遥控无人水下航行器(ROV)的运动存在时变外界干扰和系统不确定性, 利用常规滑模方法设计其运动控制器会产生抖振现象, 而常用的饱和函数联合边界层法(SatSMC)在消除抖振的同时无法保证控制精度。针对上述问题, 文中设计了super-twisting二阶滑模控制器(STSMC)来实现作业型ROV的空间路径跟踪。利用Lyapunov方法分析了系统的稳定性, 并证明该方法能够保证跟踪误差在有限时间内收敛。将提出的STSMC与SatSMC及比例-积分-微分法进行了仿真试验对比, 结果表明: STSMC能够使ROV完成对既定路径的跟踪, 并具有更好的鲁棒性、快速性和控制精度, 同时产生的抖振也明显小于SatSMC, 控制参数也未增加, 更适于ROV的实际使用。
-
关键词:
- 遥控无人水下航行器 /
- super-twisting算法 /
- 滑模控制 /
- 路径跟踪
Abstract: Time-varying external disturbances and system uncertainties affect the motion of work-class remote-operated vehicles(ROVs). The conventional sliding mode method for ROV motion control has the drawback of a chattering phenomenon, whereas the common method for eliminating chattering, namely, the saturation function combined with a boundary layer sliding mode controller(SatSMC), cannot guarantee control accuracy. To address these problems, a super-twisting second-order sliding mode controller(STSMC) is proposed to realize trajectory tracking of a work-class ROV. The Lyapunov method is used to analyze the stability of the system. It is proved that the proposed controller can ensure the convergence of a tracking error in finite time. A simulation experiment of the proposed STSMC and SatSMC methods and the proportional integral derivative(PID) control are compared. Results show that the STSMC method enables the ROV to complete the tracking of a predetermined path. This method also has stronger robustness, rapidity and accuracy. The chattering of the STSMC is also significantly reduced compared to that of the SatSMC. In addition, the control parameters are not increased, making the STSMC more suitable for actual use with ROVs. -
[1] Schjølberg I, Utne I B. Towards Autonomy in ROV Operations[J]. IFAC Papers On Line, 2015, 48(2): 183-188. [2] Ludvigsen M, S?ensen A J. Towards Integrated Autonomous Underwater Operations for Ocean Mapping and Monitoring[J]. Annual Reviews in Control, 2016, 42: 145-157. [3] Maalouf D, Chemori A, Creuze V. L1 Adaptive Depth and Pitch Control of an Underwater Vehicle with Real-Time Experiments[J]. Ocean Engineering, 2015, 98: 66-77. [4] Hoang N Q, Kreuzer E. Adaptive PD-controller for Positioning of a Remotely Operated Vehicle Close to an Underwater Structure: Theory and Experiments[J]. Control Engineering Practice, 2007, 15(4): 411-419. [5] Anderlini E, Parker G G, Thomas G. Control of a ROV Carrying an Object[J]. Ocean Engineering, 2018, 165: 307-318. [6] Huang B, Yang Q. Double-loop Sliding Mode Controller with a Novel Switching Term for the Trajectory Tracking of Work-class ROVs[J]. Ocean Engineering, 2019, 178: 80-94. [7] Baldini A, Ciabattoni L, Felicetti R, et al. Dynamic Surface Fault Tolerant Control for Underwater Remotely Operated Vehicles[J]. ISA Trans, 2018, 78: 10-20. [8] Chu Z, Zhu D, Yang S X, et al. Adaptive Sliding Mode Control for Depth Trajectory Tracking of Remotely Operated Vehicle with Thruster Nonlinearity[J]. Journal of Navigation, 2016, 70(1): 149-164. [9] 严浙平, 李响, 宋育武, 等. 参数摄动下基于积分滑模的欠驱动UUV轨迹跟踪控制方法[J]. 水下无人系统学报, 2018, 26(3): 18-24.Yan Zhe-ping, Li Xiang, Song Yu-wu, et al. Trajectory Tracking Control Method for Underactuated UUV Using Integral Sliding Mode under Parameter Perturbation[J]. Journal of Unmanned Undersea System, 2018, 26(3): 18-24. [10] 杨超, 郭佳, 张铭钧. 基于RBF神经网络的作业型AUV自适应终端滑模控制方法及实验研究[J]. 机器人, 2018, 40(3): 82-91.Yang Chao, Guo Jia, Zhang Ming-jun. Adaptive Terminal Sliding Mode Control Method Based on RBF Neural Network for Operational AUV and Its Experimental Re-search[J]. Robot, 2018, 40(3): 82-91. [11] 向先波, 陈彦彬, 杨少龙, 等. 基于联合操舵的水下航行器幂次滑模定深控制[J]. 华中科技大学学报: 自然科学版, 2018, 46(12): 126-30.Xiang Xian-bo, Chen Yan-bing, Yang Shao-long, et al. Jointed Steering Depth Control of Underwater Vehicle Based on Power Reaching Sliding Mode Algorithm[J]. J. Huazhong Univ. of Sci. & Tech. (Natural Science Edition), 2018, 46(12): 126-130. [12] Huo X, Ge T, Wang X. Horizontal Path Following Control for Deep Sea Work Class ROVs Based on a Fuzzy Logic System[J]. Ships and Offshore Structures, 2018, 13(6): 637-648. [13] Chu Z, Zhu D, Jan G E. Observer-Based Adaptive Neural Network Control for a Class of Remotely Operated Vehicles[J]. Ocean Engineering, 2016, 127: 82-89. [14] Chu Z, Zhu D, Yang S X. Observer-Based Adaptive Neural Network Trajectory Tracking Control for Remotely Operated Vehicle[J]. IEEE Transactions on Neural Networks Learning Systems, 2017, 28(7): 1633-1645. [15] Qiao L, Yi B, Wu D, et al. Design of Three Exponentially Convergent Robust Controllers for the Trajectory Tracking of Autonomous Underwater Vehicles[J]. Ocean Engineering, 2017, 134: 157-172. [16] Dai P, Lu W, Le K, et al. Sliding Mode Impedance Control for Contact Intervention of an I-AUV: Simulation and Experimental Validation[J]. Ocean Engineering, 2020, 196: 106855. [17] Slotine J J E, Li W P. Applied Nonlinear Control[M]. Beijing: China Machine Press, 2004. [18] Levant A. Homogeneity Approach to High-order Sliding Mode Design[J]. Automatica, 2005, 41(5): 823-830. [19] Casta?da H, Salas-Pe? O S, León-Morales D J. Ex-tended Observer Based on Adaptive Second Order Sliding Mode Control for a Fixed Wing UAV[J]. ISA Transactions, 2017, 66: 226-232. [20] Tuan L A, Joo Y H, Tien L Q, et al. Adaptive Neural Network Second-Order Sliding Mode Control of Dual Arm Robots[J]. International Journal of Control, Automation and Systems, 2017, 15(6): 2883-2891. [21] Liang D, Li J, Qu R, et al. Adaptive Second-Order Sliding-Mode Observer for PMSM Sensorless Control Considering VSI Nonlinearity[J]. 2017, 33(10): 8994-9004. [22] Fossen T I. Guidance and Control of Ocean Vehicles[M]. New York, USA: John Wiley & Sons Inc, 1994. [23] Lakhekar G V, Waghmare L M, Roy R G. Disturbance Observer-Based Fuzzy Adapted S-Surface Controller for Spatial Trajectory Tracking of Autonomous Underwater Vehicle[J]. IEEE Transactions on Intelligent Vehicles, 2019, 4(4): 622-36. [24] Bhat S P, Bernstein D S. Continuous Finite-time Stabilization of the Translational and Rotational Double Integrators[J]. IEEE Transactions on Automatic Control AC, 1998, 43(4): 678-681.
点击查看大图
计量
- 文章访问数: 1018
- HTML全文浏览量: 122
- PDF下载量: 139
- 被引次数: 0