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Related Experiment Video

Updated: Jun 13, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

Observer-based hierarchical distributed optimal robust safety consensus control of multi-robot systems under actuator

Zhi Li¹, Shoufeng Tang¹

¹China University of Mining and Technology, School of Information and Control Engineering, Xuzhou 221116, China.

ISA Transactions

|June 11, 2026

Summary

This study presents a robust control framework for multi-robot systems (MRS) to achieve optimal safety consensus despite noise and faults. The proposed method ensures reliable coordination and safety in complex environments.

Keywords:

Control barrier function Fault-disturbance observer Hierarchical distributed optimization Multi-robot system

Related Experiment Videos

Last Updated: Jun 13, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

Area of Science:

Robotics
Control Systems Engineering
Distributed Systems

Background:

Multi-robot systems (MRS) face challenges in achieving consensus due to environmental uncertainties like channel noise, actuator faults, and external disturbances.
Ensuring safety and optimal performance simultaneously in distributed MRS is a critical and complex problem.

Purpose of the Study:

To develop a hierarchical distributed robust safety control framework for MRS.
To address the optimal safety consensus problem under various uncertainties.
To enhance the robustness and reliability of MRS operations.

Main Methods:

A three-layer hierarchical control framework is proposed.
An upper layer features a resilient distributed optimal coordinator for noise-robust reference generation.
A middle layer utilizes a fixed-time command filter to process reference signals.
A lower layer employs an observer-based robust safety controller with a fixed-time fault-disturbance observer (FxT-FDO).
Quadratic programming (QP) is used to solve for the composite robust safety controller.

Main Results:

The proposed framework effectively generates optimal references despite channel noises.
The fixed-time command filter successfully eliminates noise impacts on reference signals.
The FxT-FDO rapidly estimates lumped uncertainties (faults and disturbances).
The composite robust safety controller ensures MRS achieve optimal safety consensus.
Simulation results validate the superior robustness of the developed control strategy.

Conclusions:

The hierarchical distributed robust safety control framework provides an effective solution for the optimal safety consensus problem in MRS.
The integration of fixed-time observers and controllers enhances system resilience against noise, faults, and disturbances.
The proposed method guarantees both safety and optimality in complex multi-robot operations.