Disturbance Rejection Control for Autonomous Trolley Collection Robots with Prescribed Performance

TL;DR

This paper presents a robust control scheme for autonomous trolley collection robots that effectively estimates disturbances and guarantees fast convergence, improving trajectory tracking in complex environments.

Contribution

It introduces a novel adaptive sliding mode disturbance observer and a prescribed performance backstepping controller for ATCR.

Findings

Effective disturbance estimation with fast convergence.

Enhanced trajectory tracking performance.

Robustness against environmental disturbances.

Abstract

Trajectory tracking control of autonomous trolley collection robots (ATCR) is an ambitious work due to the complex environment, serious noise and external disturbances. This work investigates a control scheme for ATCR subjecting to severe environmental interference. A kinematics model based adaptive sliding mode disturbance observer with fast convergence is first proposed to estimate the lumped disturbances. On this basis, a robust controller with prescribed performance is proposed using a backstepping technique, which improves the transient performance and guarantees fast convergence. Simulation outcomes have been provided to illustrate the effectiveness of the proposed control scheme.