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基于时滞估计和连续非奇异快速终端滑模控制的机器人有限时间容错控制

Finite Time Fault Tolerant Control for Robot Manipulators Using Time Delay Estimation and Continuous Nonsingular Fast Terminal Sliding Mode Control.

出版信息

IEEE Trans Cybern. 2017 Jul;47(7):1681-1693. doi: 10.1109/TCYB.2016.2555307. Epub 2016 Apr 28.

DOI:10.1109/TCYB.2016.2555307
PMID:28113571
Abstract

In this paper, a novel finite time fault tolerant control (FTC) is proposed for uncertain robot manipulators with actuator faults. First, a finite time passive FTC (PFTC) based on a robust nonsingular fast terminal sliding mode control (NFTSMC) is investigated. Be analyzed for addressing the disadvantages of the PFTC, an AFTC are then investigated by combining NFTSMC with a simple fault diagnosis scheme. In this scheme, an online fault estimation algorithm based on time delay estimation (TDE) is proposed to approximate actuator faults. The estimated fault information is used to detect, isolate, and accommodate the effect of the faults in the system. Then, a robust AFTC law is established by combining the obtained fault information and a robust NFTSMC. Finally, a high-order sliding mode (HOSM) control based on super-twisting algorithm is employed to eliminate the chattering. In comparison to the PFTC and other state-of-the-art approaches, the proposed AFTC scheme possess several advantages such as high precision, strong robustness, no singularity, less chattering, and fast finite-time convergence due to the combined NFTSMC and HOSM control, and requires no prior knowledge of the fault due to TDE-based fault estimation. Finally, simulation results are obtained to verify the effectiveness of the proposed strategy.

摘要

本文针对具有执行器故障的不确定机器人机械手,提出了一种新的有限时间容错控制(FTC)方法。首先,研究了基于鲁棒非奇异快速终端滑模控制(NFTSMC)的有限时间被动 FTC(PFTC)。为了解决 PFTC 的缺点,然后通过将 NFTSMC 与简单的故障诊断方案相结合,研究了一种 AFTC。在该方案中,提出了一种基于时滞估计(TDE)的在线故障估计算法来逼近执行器故障。利用估计的故障信息来检测、隔离和适应系统中的故障影响。然后,通过结合获得的故障信息和鲁棒 NFTSMC,建立了一种鲁棒的 AFTC 律。最后,采用基于超扭曲算法的高阶滑模(HOSM)控制来消除抖振。与 PFTC 和其他最先进的方法相比,由于结合了 NFTSMC 和 HOSM 控制,所提出的 AFTC 方案具有高精度、强鲁棒性、无奇异、较少抖振和快速有限时间收敛等优点,并且由于基于 TDE 的故障估计,不需要事先了解故障。最后,通过仿真结果验证了所提出策略的有效性。

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