基于事件触发的水下滑翔机自适应容错俯仰控制

doi:10.12382/bgxb.2022.0234

摘要/Abstract

摘要：

为确保水下滑翔机俯仰姿态控制对模型不确定性及执行器故障的鲁棒性并降低控制能耗,提出一种基于事件触发的自适应容错俯仰控制算法。在反步控制的基础上,使用动态面技术避免对虚拟控制律求导;利用基于历史输入、输出数据的径向基神经网络对模型不确定项、环境扰动和执行器故障进行逼近与补偿;设计基于相对阈值的事件触发条件,避免控制律的连续更新,从而降低控制能耗。使用Lyapunov稳定性理论证明了闭环系统的所有信号满足半全局一致最终有界。仿真实验结果表明,所设计的控制器在实现鲁棒性的前提下进一步节约了控制能耗和通信资源。

关键词: 海洋工程, 水下滑翔机, 事件触发控制, 自适应控制

Abstract:

To ensure robustness against model uncertainties and actuator faults while reducing control energy consumption, this paper proposes a robust adaptive fault-tolerant scheme using the event-triggered input technique for the pitch attitude control of underwater gliders. Based on the backstepping method, the dynamic surface control technique is employed to avoid calulating the derivation of the virtual control law. Model uncertainties, external disturbances, and actuator faults are compensated as a whole using a RBF-NN that takes advantage of historical input and output data. A relative-threshold event-triggered condition is designed to avoid continuous updating of the control law. Finally, the Lyapunov stability theory is used to ensure the SGUUB of the closed-loop signals. The simulation results confirm that the proposed scheme has robust control performance and can better reduce control energy consumption and communication resource occupation.

Key words: ocean engineering, underwater glider, event-triggered control, adaptive control

闵博旭, 高剑, 井安言, 陈依民, 王佳润, 潘光. 基于事件触发的水下滑翔机自适应容错俯仰控制[J]. 兵工学报, 2023, 44(7): 2092-2100.

MIN Boxu, GAO Jian, JING Anyan, CHEN Yimin, WANG Jiarun, PAN Guang. Robust Event-triggered Adaptive Pitch Attitude Control for Underwater Gliders with Actuator Faults[J]. Acta Armamentarii, 2023, 44(7): 2092-2100.

图/表 6

图1 水下滑翔机运动坐标系

Fig.1 Coordinate system for a moving underwater glider (UG)

图2 俯仰角控制效果

Fig.2 Control effect of UG’s pitch angle

图3 滑块位置

Fig.3 Position of the moving mass

图4 水下滑翔机纵向运动轨迹

Fig.4 Trajectory of UG in vertical plane

图5 事件触发间隔

Fig.5 Event trigger intervals

图6 复合不确定项及神经网络逼近效果

Fig.6 Compound uncertainties and NN approximation effect

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