Adaptive Fuzzy Finite Time Control of Robot Systems with Prescribed Performance

被引：0

作者：

Liu, Zhuang ^{[1
]}

Zhao, Yue ^{[1
]}

Liu, Fagang ^{[2
]}

Gao, Song ^{[3
]}

Sun, Yizhuo ^{[1
]}

Wang, Jiahui ^{[4
]}

机构：

[1] Harbin Inst Thchnol, Dept Control Sci & Engn, Harbin, Peoples R China

[2] State Grid Heilongjiang Elect Power Co Ltd, Suihua Power Supply Co, Suihua, Peoples R China

[3] Shanghai Acad Spaceflight Technol, Aerosp Syst Engn Shanghai, Shanghai, Peoples R China

[4] Harbin Engn Univ, Coll Automat, Harbin, Peoples R China

来源：

PROCEEDINGS OF 2021 IEEE 30TH INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE) | 2021年

关键词：

Adaptive fuzzy control; BLF; prescribed tracking performance; DO; finite time control; MIMO NONLINEAR-SYSTEMS; TASKS;

D O I：

10.1109/ISIE45552.2021.9576362

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In this paper, an adaptive fuzzy logic controller based on disturbance observer is studied for robot systems with guaranteed prescribed performances and parametric uncertainties. An adaptive fuzzy logic system (FLS) is employed to approximate the unknown dynamic parts of the robotic manipulators, and a disturbance observer (DO) is constructed to attenuate the influence of the unknown disturbances from humans and environment. Barrier Lyapunov function (BLF) is used to guaranteed prescribed transient and steady-state tracking control performances. And with the use of Lyapunov stability theory, the tracking errors are proved to be semiglobally finite-time stable (SGFTS). Simulation is carried out to verify the effectiveness and usefulness of the proposed method.

引用

页数：6

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