Prescribed‐time stabilisation control of differential driven automated guided vehicle

The position control problem of differential‐driven automated guided vehicles (AGVs) based on the prescribed‐time control method is studied. First, an innovative orientation error function is proposed by an auxiliary arcsine function about the orientation angle. Thus, the problem of position control...

Full description

Saved in:
Bibliographic Details
Published in:IET cyber-systems and robotics 2023-03, Vol.5 (1), p.n/a
Main Authors: Chen, Qiyuan, Zhang, Pengfei
Format: Article
Language:English
Subjects:
Automated guided vehicle
Automated guided vehicles
Automatic control
Automation
Closed loop systems
Constraints
Control methods
Control systems
Control theory
Controllers
Error analysis
Error functions
kinematic system
Kinematics
Orientation
Parameters
position control
prescribed‐time
Risk management
Smoothness
stabilisation
Upper bounds
Vehicles
Velocity
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The position control problem of differential‐driven automated guided vehicles (AGVs) based on the prescribed‐time control method is studied. First, an innovative orientation error function is proposed by an auxiliary arcsine function about the orientation angle. Thus, the problem of position control of AGV is transformed into the stabilisation control of the kinematic system. Second, by introducing a reserved time parameter and a smooth switching function, a novel time‐varying scaling function is proposed. This novel scaling function avoids the risk of infinite gain in the conventional prescribed‐time control method while ensuring the smoothness of control laws. Then, an improved velocity constraint function is proposed using the Gaussian function. Compared with the existing constraint function, the proposed method not only has more smoothness but also solves the balance point errors caused by the large AGV orientation errors. The presented method ensures that the AGV reaches the target position in a prescribed time. Hence, the upper bound of the AGV system state can be determined by adjusting parameters. Matlab simulation results show that the proposed controller can effectively make the AGV system state satisfy the prescribed bound.
ISSN:2631-6315
2631-6315
DOI:10.1049/csy2.12067