Adaptive fuzzy control of mobile robots with full-state constraints and unknown longitudinal slipping

被引：12

作者：

Nie, Jingmou ^{[1
]}

Wang, Yaonan ^{[1
]}

Miao, Zhiqiang ^{[1
]}

Jiang, Yiming ^{[1
]}

Zhong, Hang ^{[1
]}

Lin, Jie ^{[1
]}

机构：

[1] Hunan Univ, Coll Elect & Informat Engn, Changsha 410082, Peoples R China

来源：

NONLINEAR DYNAMICS | 2021年 / 106卷 / 04期

基金：

中国博士后科学基金;

关键词：

Adaptive control; Wheeled mobile robot; Barrier Lyapunov Fuction (BLF); Full-state constraints; Fuzzy system; Trajectory tracking; BARRIER LYAPUNOV FUNCTIONS; FEEDBACK TRACKING CONTROL; NEURAL-NETWORK CONTROL; NONLINEAR-SYSTEMS; SLIDING-MODE; DESIGN; DELAY; MANIPULATORS;

D O I：

10.1007/s11071-021-06933-y

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Motion control of wheeled mobile robots with state constraints under slipping condition faces many difficulties, such as unmeasurable velocities, non-holonomic kinematic model, and unknown disturbances. Aiming at these problems, an adaptive fuzzy controller is proposed in this paper. Firstly, a fuzzy state observer is developed to estimate the velocity and compensate the unknown complex system model. Then, a output vector is designed to convert the position constraint to output constraints, and a Barrier Lypunov Function is constructed to ensure the motion constraint. Moreover, a simpler longitudinal slipping model that allows handling of longitudinal sliding more conveniently is further designed. The stability of the closed-loop system is analyzed by the Lyapunov theorem. Finally, simulation and experiment verify the effectiveness and practicality of the method under the longitudinal slipping situation, reflecting the suppression effect on tracking errors.

引用

页码：3315 / 3330

页数：16

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