A leader-following consensus problem of multi-agent systems in heterogeneous networks

Cruz-Ancona, Christopher D.; Martínez-Guerra, Rafael; Pérez-Pinacho, Claudia A.

doi:10.1016/j.automatica.2020.108899

Cited by 24 publications

(7 citation statements)

References 29 publications

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“…Theorem 3. Consider the MAS (19) with the controller (20) and the control gains ( 21)- (22). If Assumptions 1-3 hold, for any > 0, there exists a finite time t such that the consensus is nontrivially solved for t ≥ t.…”

Section: Adaptive Sliding Mode For Multi-agent Systems With General Dyanmicsmentioning

confidence: 99%

“…In References 20-22, the leaderless consensus and leader-following consensus problems were considered for MASs with heterogeneous dynamics. All these efforts [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22] focused on the consensus of MASs in ideal environments. However, in practical MASs, the external disturbances are unavoidable and the system performance is always affected.…”

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confidence: 99%

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Distributed consensus for multi‐agent systems via adaptive sliding mode control

Jiang

et al. 2021

Intl J Robust & Nonlinear

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This article considers the consensus of multi-agent systems (MASs) with external disturbances by using sliding mode control. First, by establishing a novel sliding mode surface and designing a sliding mode control protocol with constant gains, the consensus of MASs with unknown bounded disturbances is studied. Second, based on the barrier function, a new type of adaptive sliding mode switching protocol is proposed, in which the control gains can be chosen randomly and the upper bound of the disturbance does not need to be known in a prior. By using this protocol, the consensus error can converge to any given region of zero in finite time. Moreover, the leaderless consensus and leader-following tracking problem of MASs with general dynamics and external disturbances are also investigated via extending the proposed adaptive sliding mode protocol. Finally, some examples are presented to illustrate the effectiveness of the control strategies. K E Y W O R D Sadaptive sliding mode control, consensus, multi-agent systems, unknown disturbances INTRODUCTIONCooperation behaviors such as flocking of birds, schooling of fish, and swarming in insects, exist in the human society extensively. Inspired by these phenomena, the study on cooperative control of multi-agent systems (MASs) has drawn significant attention of diverse research community over the past decades. The main potential applications include unmanned air vehicles, robotic teams, sensor networks, formation control, and so on. [1][2][3][4] The consensus is a fundamental problem of MASs and the main task is to design some distributed protocols such that all agents converge to a common state. The basic framework of the consensus was constructed in Reference 5. Since then, many useful schemes have been used to design the consensus protocols and a lot of fruitful results have been obtained. For instance, feedback control, 6,7 intermittent control, 8,9 impulsive control, 10,11 sample-data control, 12,13 event-triggered control, [14][15][16] adaptive control [17][18][19] and so on. In these works, the MASs with homogeneous dynamics were considered. In References 20-22, the leaderless consensus and leader-following consensus problems were considered for MASs with heterogeneous dynamics. All these efforts [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22] focused on the consensus of MASs in ideal environments. However, in practical MASs, the external disturbances are unavoidable and the system performance is always affected. Hence, the study on consensus of MASs with external disturbances is very important and necessary.In this article, we address the consensus of MASs with external disturbances. In existing works, the external disturbances can be roughly divided into two categories: the disturbance is generated by an external linear autonomous system [Correction added on 19 July 2021, after first online publication: the Funding information section has been corrected in this version.]

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Section: Adaptive Sliding Mode For Multi-agent Systems With General Dyanmicsmentioning

confidence: 99%

mentioning

confidence: 99%

Distributed consensus for multi‐agent systems via adaptive sliding mode control

Jiang

et al. 2021

Intl J Robust & Nonlinear

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“…The most basic formation consists of two robots and is commonly referred to as the leader-follower scheme [15][16][17], in which the leader robot is assigned to follow a predefined smooth trajectory in the plane and the follower must maintain a relative posture concerning the leader. The type of mobile robots mostly seen in leader-follower control tasks are differential-drive [18] and omnidirectional [19] mobile robots, but some works, like [20], combine the two in rigid body behaviors.…”

Section: Introductionmentioning

confidence: 99%

Leader–Follower Formation and Disturbance Rejection Control for Omnidirectional Mobile Robots

Ramírez-Neria,

González-Sierra,

Madonski

et al. 2023

Robotics

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This paper proposes a distance-based formation control strategy with real-time disturbance rejection for omnidirectional mobile robots. The introduced control algorithm is designed such that the leader tracks a desired trajectory while the follower keeps a desired distance and formation angle concerning the leader. In the first step, the evolution of distance and formation angle is obtained from a perturbed second-order dynamic model of the robot, aided by a general proportional integral observer (GPIO), added to estimate unwanted disturbances. Then, the control law is designed for both robots via the active disturbance rejection control (ADRC) methodology, which only depends on the position, distance, and orientation measurements. A numerical simulation compared with a robust controller exhibits the system’s behavior. Furthermore, a set of laboratory experiments is conducted to verify the performance of the proposed control system, where a motion capture system is used as a proof of concept. In this context, this is considered a previous step for further experimentation with onboard sensors.

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“…For example, the unmanned aerial vehicles (UAVs) need to move by the preplanned sailing route or a manual instruction coming from the commander on the ground. Hence, the leader-following synchronization problems have been investigated by designing the appropriate controller such that all nodes synchronize to the manifold of a prescribed leader (Cruz-Ancona et al, 2020; Gao et al, 2017). The leader plays the role of an external input providing the reference path for the network to arrive at the predefined destination.…”

Section: Introductionmentioning

confidence: 99%

Fixed-time leader-following synchronization in delayed network via non-chattering nonlinear control

Yan

et al. 2022

Transactions of the Institute of Measurement and Control

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The fixed-time leader-following synchronization in a non-identical delayed network via non-chattering nonlinear control is investigated. By introducing a function of control error, a continuous and differential controller is constructed without using the sign function and absolution of the error. The sufficient conditions are then established to guarantee that synchronization errors converge exactly to zero within a fixed time interval. The proposed approach provides a high convergence for the network accurately tracking the trajectory of the leader. More importantly, a tighter bound for the settling time is obtained and the chattering effects are eliminated. The numerical simulations are conducted to illustrate the effectiveness of theoretical analysis.

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A leader-following consensus problem of multi-agent systems in heterogeneous networks

Cited by 24 publications

References 29 publications

Distributed consensus for multi‐agent systems via adaptive sliding mode control

Distributed consensus for multi‐agent systems via adaptive sliding mode control

Leader–Follower Formation and Disturbance Rejection Control for Omnidirectional Mobile Robots

Fixed-time leader-following synchronization in delayed network via non-chattering nonlinear control

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