Reliability analysis of a multi-eso based control strategy for level adjustment control system of quadruped robot under disturbances and failures
The complexity of control algorithms and their vulnerability to disturbances and failures are the main problems that restrict the operations of multi-legged mobile robots in more complex environments. In this paper, a multiple extended state observer (ESO) based control strategy is proposed to achie...
Gespeichert in:
Veröffentlicht in: | Eksploatacja i niezawodność 2020-01, Vol.22 (1), p.42-51 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The complexity of control algorithms and their vulnerability to disturbances and failures are the main problems that restrict the
operations of multi-legged mobile robots in more complex environments. In this paper, a multiple extended state observer (ESO)
based control strategy is proposed to achieve stable tilt angle control for quadruped robots under the influence of disturbances
and actuator failures. By treating the multiple legs as parallel control objects, more ESOs were added to improve the disturbance
rejection ability of the linear active disturbance rejection control (LADRC). Correlation of interactive information about the legs
is realized by the synthesis of multiple ESO information. Based on LADRC, this method has the advantages of easy parameter
tuning, good robustness, and strong ability to cope with interference and fault conditions. A control system reliability evaluation
method was proposed. The reliability and control performance of the multi-ESO based control system under leg stuck failure conditions were systematically analyzed. Simulation and experimental results for the level adjustment control system of a quadruped
robot are provided to verify the disturbance rejection ability, feasibility and practicability of the proposed multi-ESO based control
method |
---|---|
ISSN: | 1507-2711 2956-3860 |
DOI: | 10.17531/ein.2020.1.6 |