Distributed Tracking of Leader-Follower Multiagent Systems Subject to Disturbed Leader’s Information

Li, Xiangyang; Xu, S. K.; Gao, Huanli; Cai, He

doi:10.1109/access.2020.3045760

Cited by 10 publications

(2 citation statements)

References 40 publications

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“…The formation control problem can be defined by a shape or a relative state. The first component of MAS dictates the position of the leader, and the second component of MAS corresponds to the overall formation (followers) [24]. The dynamics of a MAS is represented by three sets of differential and algebraic equations that correspond to the leader, followers, and the formation error model.…”

Section: Preliminariesmentioning

confidence: 99%

HDP Algorithms for Trajectory Tracking and Formation Control of Multi-Agent Systems

2022

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A heuristic dynamic programming (HDP) algorithm for trajectory tracking and formation control of multi-agent systems (MAS) is presented in this paper. The selected HDP method allows for an online optimal control design. The multi-agent control problem is formulated as a leader-follower, where it is necessary for followers to maintain the assigned formation, while the leader follows the specified trajectory. Developed QR-Solver and RLS µ -QR-HDP-DLQR algorithms provide a new methodology to obtain the solution of the Hamilton-Jacobi-Bellman (HJB) equation. These proposed solutions are based on QR factorization to decrease the computational cost and avoid issues associated with numerical stability of conventional least squares (LS) method. The algorithms' performances such as convergence, numerical stability, and computational metrics, were experimentally evaluated for two control systems: aerial altitude control (one degree of freedom) and terrestrial robot (two degrees of freedom).

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Section: Preliminariesmentioning

confidence: 99%

HDP Algorithms for Trajectory Tracking and Formation Control of Multi-Agent Systems

2022

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“…e multiple mobile robots also enhance the fault tolerance and robustness of the system and strengthen the ability of robots' environment recognition. Comparing with the leader-follower method [5][6][7][8], behavior-based method [9][10][11],and virtual structure method [12,13], the model predictive control (MPC) has attracted attention because of its ability of improving the robustness of the system and having better dynamic control performance in solving the problem of consensus protocol in distributed formation control of multiple mobile robots. Also, MPC is convenient to establish the system model.…”

Section: Introductionmentioning

confidence: 99%

A Distributed Model Predictive Control for Multiple Mobile Robots with the Model Uncertainty

Shang

Zhu

Pan

et al. 2021

Discrete Dynamics in Nature and Society

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In this paper, a distributed predictive control with the model uncertainty which uses the data-driven strategy and robust theory (data-driven RDMPC) is proposed for the formation control of multiple mobile robots. The robust performance objective minimization is applied to replace the quadratic performance objective minimization to establish the optimization problem, where the model uncertainty is considered in the distributed system. The control policy is derived by applying the data-driven strategy, and the future predictive value is obtained by employing the linear law in the historical data. Lyapunov theory is referred to analyze the stability of the mobile robot formation system. The effectiveness of the proposed method is proved by a set of simulation experiments.

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Hierarchical Formation by the Cooperative Output Regulation Approach

Cai

Gao

2022

Proceedings of 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control

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Distributed Tracking of Leader-Follower Multiagent Systems Subject to Disturbed Leader’s Information

Cited by 10 publications

References 40 publications

HDP Algorithms for Trajectory Tracking and Formation Control of Multi-Agent Systems

HDP Algorithms for Trajectory Tracking and Formation Control of Multi-Agent Systems

A Distributed Model Predictive Control for Multiple Mobile Robots with the Model Uncertainty

Hierarchical Formation by the Cooperative Output Regulation Approach

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