Robust Observer-based Leader-Following Consensus for Multi-agent Systems

Trejo, Jesus A. Vazquez; Medina, Manuel Adam; Trejo, Juan Antonio Vazquez; Beltrán, Carlos Daniel García; Morales, Jarniel García

doi:10.1109/tla.2021.9475849

Cited by 11 publications

(5 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Additionally, the variety of control algorithms available in the literature for MRS is wide. In this way, for formation problems by consensus or leader-follower (one of the most studied for MRS), it is possible to find studies focused on the most traditional control algorithms such as Proportional Integral Derivative (PID) controllers [11] or Linear-Quadratic Regulator (LQR) [12] or in more complex algorithms such as robust control [13], predictive control [14], intelligent control through neural networks [15] or genetic algorithms [16].…”

Section: Introductionmentioning

confidence: 99%

Robotic Park: Multi-Agent Platform for Teaching Control and Robotics

et al. 2023

View full text Add to dashboard Cite

Multi-agent system research is a hot topic in different application domains. In robotics, multi-agent robot systems (MRS) can realize complex tasks even if the behavior of each individual agent seems simple thanks to the cooperation between them. Although many control algorithms for MRS are proposed, few experimental results are validated on real data, being essential to building new testbeds to conduct MRS research and teaching. Moreover, most existing platforms for experimentation do not offer an overall solution allowing software and hardware design tools. This paper describes the design and operation of Robotic Park, a new indoor experimental platform for research in multi-agent systems. The heterogeneity and flexibility of its configuration are two of its main features. It supports control strategies design and validation of MRS algorithms. Experiences can be carried out in a virtual environment, in a physical environment, or under a hybrid scheme, as digital twins have been developed in Gazebo and Webots. Currently, two types of aerial vehicles, the Crazyflie 2.X and the DJI Tello, are available. It also includes two types of differential mobile robots, the Turtlebot3 and the Khepera IV. Both internal and external positioning systems using different technologies such as Motion Capture or Ultra-WideBand are also available for experiences. All components are connected through ROS2 (Robot Operating System 2) which enables experiences under a centralized, distributed, or hybrid scheme, and different communication strategies can be implemented. A mixed reality experience that addresses the problem of formation control using event-based control illustrates the platform usage.

show abstract

Section: Introductionmentioning

confidence: 99%

Robotic Park: Multi-Agent Platform for Teaching Control and Robotics

et al. 2023

View full text Add to dashboard Cite

show abstract

“…The second category is the distributed control method, where each UAV exchanges information only with its neighbors. The leader-follower scheme [6][7][8][9][10] selects leader UAVs, and the remaining followers update their locations by exchanging information with the nearest leader. However, this method has poor robustness.…”

Section: Introductionmentioning

confidence: 99%

A Scalable Distributed Control Algorithm for Bearing-Only Passive UAV Formation Maintenance

Gao

Feng

Chen

et al. 2023

Sensors

View full text Add to dashboard Cite

Unmanned Aerial Vehicles (UAVs) can cooperate through formations to perform tasks. Wireless communication allows UAVs to exchange information, but for the situations requiring high security, electromagnetic silence is needed to avoid potential threats. The passive UAV formation maintenance strategies can fulfill the requirement of electromagnetic silence at the cost of heavy real-time computing and precise locations of UAVs. To pursue high real-time performance without the localization of UAVs, this paper proposes a scalable distributed control algorithm for bearing-only passive UAV formation maintenance. By minimizing necessary communication, pure angle information is applied to maintain UAV formations through distributed control, without the knowledge of the UAVs’ precise locations. The convergency of the proposed algorithm is proven strictly and the converging radius is derived. Through simulation, the proposed algorithm is proven to be suitable for a general case and demonstrates fast convergence speed, strong anti-interference capability, and high scalability.

show abstract

“…5 Subsequently, many scholars pay attention to analyze the system optimality when studying the consensus problem for linear MAS. 6,7 The distributed state feedback controller is put forward to guarantee that agent outputs converge to the optimal solution, 6 and a robust optimal controller is extended to propose for linear MAS with external disturbances. 7 Note that most real systems are complicated nonlinear systems, which are usually hard to approximate by linear MAS.…”

Section: Introductionmentioning

confidence: 99%

“…6,7 The distributed state feedback controller is put forward to guarantee that agent outputs converge to the optimal solution, 6 and a robust optimal controller is extended to propose for linear MAS with external disturbances. 7 Note that most real systems are complicated nonlinear systems, which are usually hard to approximate by linear MAS. Hence, further studies are needed to deal with the optimal consensus issue for nonlinear MAS.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Neural network–based optimal fault compensation control of the nonlinear multi-agent system and its application to UAVs formation flight

Duan

Liu

Dai³

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

View full text Add to dashboard Cite

This article investigates the optimal consensus problem for unmanned aerial vehicle formation systems with actuator faults based on nonlinear multi-agent systems. Initially, for fault-free multi-agent system, the distributed optimal controllers are constructed based on the adaptive dynamic programming technique. A critic neural network is applied to approximate the solution of the nonlinear Hamilton–Jacobi–Bellman equations, in which the weight updating laws are built to guarantee the weight vectors of the critic neural network convergence. Second, the fault compensators and corresponding tuning laws are proposed to compensate for actuator faults. Through a combination of optimal controllers and fault compensators, the distributed optimal fault-tolerant controllers are obtained. Then, according to Lyapunov extension theorem, some stability criteria for ensuring the stability of the aircraft and the normal flight of the unmanned aerial vehicle formation are established in the event of an actuator failure. Finally, an example of an unmanned aerial vehicle formation system is introduced to verify the efficiency and reliability of the designed optimal fault-tolerant control scheme.

show abstract

Robust Observer-based Leader-Following Consensus for Multi-agent Systems

Cited by 11 publications

References 37 publications

Robotic Park: Multi-Agent Platform for Teaching Control and Robotics

Robotic Park: Multi-Agent Platform for Teaching Control and Robotics

A Scalable Distributed Control Algorithm for Bearing-Only Passive UAV Formation Maintenance

Neural network–based optimal fault compensation control of the nonlinear multi-agent system and its application to UAVs formation flight

Contact Info

Product

Resources

About