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Journal of Zhejiang University SCIENCE A
ISSN 1673-565X(Print), 1862-1775(Online), Monthly
2023 Vol.24 No.9 P.749-761
Finite-time path following control of a sailboat with actuator failure and unknown sideslip angle
Abstract: Suffering from actuator failure and complex sideslip angle, the motion control of a sailboat becomes challenging. In this paper, an improved double finite-time observer-based line-of-sight guidance and finite-time control (IDFLOS-FC) scheme is presented for path following of sailboats. The salient features of the proposed IDFLOS-FC scheme are as follows: (1) Considering the problem of actuator failure, an actuator failure model is introduced into the dynamics model of a sailboat. (2) The time-varying sideslip angle of the sailboat is accurately observed by the double finite-time sideslip observers (DFSOs), which reduces the error in line-of-sight (LOS) guidance. (3) A radial basis function (RBF) neural network is used to fit the uncertainty of the model, and the upper bound of the sum of fault effects and external disturbances is estimated based on adaptive theory, so that the controller has accurate tracking and interference suppression. (4) According to the Lyapunov method, the system is finite-time stable. Finally, simulation was used to validate the effectiveness of the method.
Key words: Sailboat; Sideslip angle; Sideslip angle observer; Finite-time control (FC); Path following
机构:1哈尔滨工程大学,水下机器人重点实验室,中国哈尔滨,150001;2大连海事大学,海洋工程学院,中国大连,116026
目的:在实际航行中,无人帆船存在执行器故障问题以及未知漂角,使得帆船的路径跟踪变得极具挑战性。本文考虑了无人帆船的执行器故障,并设计了一种有限时间漂角观测器来观测未知漂角,以提高无人帆船的路径跟踪精度。
创新点:1.设计双有限时间漂角观测器,能够观测时变的漂角,适用于更复杂的工况;2.设计一种参数自适应调整的非奇异终端滑模,用以增强系统的鲁棒性;3.采用RBF神经网络最小参数估计法对无人帆船模型的不确定性部分进行估计,设计一种基于自适应参数调整滑模的容错控制方法,并证明航向控制系统的误差具有有限时间收敛性。
方法:1.设计双有限时间漂角观测器,用于观测未知漂角;2.考虑执行器故障,利用反步法与滑模控制法,推导出合适的控制律;3.通过仿真模拟,中途增加故障的方式来证实所设计方案的鲁棒性和可靠性。
结论:1.所设计的双有限时间漂角观测器能够精确观测对未知漂角;2.所提出的IDFLOS-FC方案能在执行器失效、漂角随时间变化和未知外部扰动的条件下实现无人驾驶帆船的精确路径跟踪,并能在添加故障时精确跟踪所需的路径,这充分证明了IDFLOS-FC方案的可靠性和优越性。
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DOI:
10.1631/jzus.A2300184
CLC number:
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On-line Access:
2023-06-20
Received:
2023-04-08
Revision Accepted:
2023-07-08
Crosschecked:
2023-09-20