Rotary enclosing control of second-order multi-agent systems for a group of targets

Shi, Yahui; Li, R.; Teo, K.L.

doi:10.1080/00207721.2016.1144226

Cited by 25 publications

(3 citation statements)

References 23 publications

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“…Proof: (13) Choose the Lyapunov function candidate as V 1s = 1 2 ξ H s ξ s . Then, we obtain the time derivative of V s along system (13) with the inequalities in Lemma 2.…”

Section: Moreover L(a 1 ) and L(a 2 ) Denote The Laplacian Matrices mentioning

confidence: 99%

Distributed Multi-Target Rotating Encirclement Control of Second-Order Multi-Agent Systems With Nonconvex Input Constraints

Zhang

Ling

2020

IEEE Access

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This paper investigates the collective multi-target rotating encirclement formation problem of second-order multi-agent systems, where the inputs are constrained in nonconvex sets. The objective requires that all agents rotate around targets' geometric center with the desired radius and angular velocity. Firstly, the targets' geometric center and rotating radius are calculated by two distributed fixed-time estimators based on the neighbors' information. Then, with the complex domain theory, we construct two consensus vectors complying with the conditions of the multi-target rotating encirclement formation, and propose a distributed multi-target rotating encirclement control scheme to force all agents achieve the desired formation structure. Moreover, a sufficient condition is provided for choosing design parameters with the aid of Lyapunov theory. In order to handle the problem caused by the nonconvex input constraints, a constraint operator is introduced to ensure all control inputs always lie in the corresponding nonconvex sets. Finally, numerical simulation results are presented to demonstrate the effectiveness and correctness of our theoretical control scheme. INDEX TERMS Rotating encirclement control, nonconvex input constraints, distributed estimator, second-order multi-agent systems.

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“…Proof: (13) Choose the Lyapunov function candidate as V 1s = 1 2 ξ H s ξ s . Then, we obtain the time derivative of V s along system (13) with the inequalities in Lemma 2.…”

Section: Moreover L(a 1 ) and L(a 2 ) Denote The Laplacian Matrices mentioning

confidence: 99%

Distributed Multi-Target Rotating Encirclement Control of Second-Order Multi-Agent Systems With Nonconvex Input Constraints

Zhang

Ling

2020

IEEE Access

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“…This effectively reduces the measuring burden and relieves the payload of the mobile robot. For this purpose, many efforts have been made for the solution to the localization and circumnavigation problem by using distance‐only measurements, 14‐16 bearing‐only measurements, 17‐19 and received signal strength (RSS) measurements 20‐23 . In particular, by using the continuous distance measurement with respect to the target, the authors of References 15 and 16 proposed feasible control algorithms such that the concerned mobile agent was capable of localizing and circumnavigating the target as prescribed.…”

Section: Introductionmentioning

confidence: 99%

“…For this purpose, many efforts have been made for the solution to the localization and circumnavigation problem by using distance‐only measurements, 14‐16 bearing‐only measurements, 17‐19 and received signal strength (RSS) measurements 20‐23 . In particular, by using the continuous distance measurement with respect to the target, the authors of References 15 and 16 proposed feasible control algorithms such that the concerned mobile agent was capable of localizing and circumnavigating the target as prescribed. By just implementing the bearing measurement with respect to the target, a localization and circumnavigation control strategy was proposed for a holonomic robot in Reference 17 and then an extension scheme was put forward for a non‐holonomic robot in Reference 19.…”

Section: Introductionmentioning

confidence: 99%

Stationary target localization and circumnavigation by a non‐holonomic differentially driven mobile robot: Algorithms and experiments

Wang

Zou

Meng

2020

Intl J Robust & Nonlinear

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Summary This article addresses a surveillance problem where the goal is to achieve a circular motion around a target by a non‐holonomic differentially driven mobile robot. The available information for the mobile robot includes its own position, velocity with respect to the inertial frame, and the bearing angle of the target in its body frame. Since the target position is unavailable, an estimator is first proposed to localize it. Then a two‐step controller is given to drive the mobile robot to move onto a circular trajectory with a desired radius around it. It is shown that the proposed algorithm guarantees the convergence of the estimation error to a small neighborhood of zero and the motion of the robot to a small neighborhood of a designed radius. The performance of the proposed algorithm is first verified by simulations. Then, several experiments on a differentially driven mobile robot, Pioneer 3‐DX, are presented to further validate the proposed algorithm.

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MADDPG: Multi-agent Deep Deterministic Policy Gradient Algorithm for Formation Elliptical Encirclement and Collision Avoidance

Chen

Liu³

et al. 2022

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

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Rotary enclosing control of second-order multi-agent systems for a group of targets

Cited by 25 publications

References 23 publications

Distributed Multi-Target Rotating Encirclement Control of Second-Order Multi-Agent Systems With Nonconvex Input Constraints

Distributed Multi-Target Rotating Encirclement Control of Second-Order Multi-Agent Systems With Nonconvex Input Constraints

Stationary target localization and circumnavigation by a non‐holonomic differentially driven mobile robot: Algorithms and experiments

MADDPG: Multi-agent Deep Deterministic Policy Gradient Algorithm for Formation Elliptical Encirclement and Collision Avoidance

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