A Distributed Optimization Algorithm for Fixed-Time Flocking of Second-Order Multiagent Systems

Chen, Jianing; Yang, Yong; Qin, Sitian

doi:10.1109/tnse.2023.3292860

Cited by 7 publications

(3 citation statements)

References 36 publications

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“…With this reason in mind, many methods are constructed for secondorder MASs due to the widely use in practice [20][21][22][23]. In [24], a decentralized optimization control protocol with fixed-time flocking is developed for second-order MASs where the networks are time-varying. Ref.…”

Section: Introductionmentioning

confidence: 99%

“…Besides, each agent in the FOMASs is described by nonstrict-feedback MIMO dynamics, which is more general and complex to design the control protocol. (2) Different from [16][17][18][19][20][21][22][23][24][25][26], where the DOPs are investigated for first-order or secondorder MASs, this paper dedicates to solve the fractional high-order DOP, which means that MASs and the DOP in this paper are close to the engineering systems. Besides, the MASs in this paper includes nonlinear uncertain terms in each order.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Adaptive Optimization Algorithm for Fractional High-Order Multiagent Systems Based on Event-Triggered Strategy and Input Quantization

Yang,

Yuan,

Chen

et al. 2023

Fractal Fract

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This paper investigates the distributed optimization problem (DOP) for fractional high-order nonstrict-feedback multiagent systems (MASs) where each agent is multiple-input–multiple-output (MIMO) dynamic and contains uncertain dynamics. Based on the penalty-function method, the consensus constraint is eliminated and the global objective function is reconstructed. Different from the existing literatures, where the DOPs are addressed for linear MASs, this paper deals with the DOP through using radial basis function neural networks (RBFNNs) to approximate the unknown nonlinear functions for high-order MASs. To reduce transmitting and computational costs, event-triggered scheme and quantized control technology are combined to propose an adaptive backstepping neural network (NN) control protocol. By applying the Lyapunov stability theory, the optimal consensus error is proved to be bounded and all signals remain semi-global uniformly ultimately bounded. Simulation shows that all agents reach consensus and errors between agents’ outputs and the optimal solution is close to zero with low computational costs.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Adaptive Optimization Algorithm for Fractional High-Order Multiagent Systems Based on Event-Triggered Strategy and Input Quantization

Yang,

Yuan,

Chen

et al. 2023

Fractal Fract

View full text Add to dashboard Cite

show abstract

“…Recently decentralized optimization has gained significant popularity in numerous fields due to its promising applications in areas such as large-scale machine learning, distributed control, decentralized estimation, smart grids, and more [1][2][3][4][5][6][7]. This work focuses on addressing the decentralized optimization problem min…”

Section: Introductionmentioning

confidence: 99%

Distributed Primal-Dual Mirror Dynamics for Constraint-Coupled Optimization

2023

Lecture Notes in Electrical Engineering

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We propose an inexact decentralized dual gradient tracking method (iDDGT) for decentralized optimization problems with a globally coupled equality constraint. Unlike existing algorithms that rely on either the exact dual gradient or an inexact one obtained through single-step gradient descent, iDDGT introduces a new approach: utilizing an inexact dual gradient with controllable levels of inexactness. Numerical experiments demonstrate that iDDGT achieves significantly higher computational efficiency compared to state-of-the-art methods. Furthermore, it is proved that iDDGT can achieve linear convergence over directed graphs without imposing any conditions on the constraint matrix. This expands its applicability beyond existing algorithms that require the constraint matrix to have full row rank and undirected graphs for achieving linear convergence.

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Fixed-time consensus control for uncertain heterogeneous multi-agent systems with high-order dynamics and time-varying delay under generic topologies

Elahi,

Alfi,

Chadli

2024

Mathematics and Computers in Simulation

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A Distributed Optimization Algorithm for Fixed-Time Flocking of Second-Order Multiagent Systems

Cited by 7 publications

References 36 publications

Distributed Adaptive Optimization Algorithm for Fractional High-Order Multiagent Systems Based on Event-Triggered Strategy and Input Quantization

Distributed Adaptive Optimization Algorithm for Fractional High-Order Multiagent Systems Based on Event-Triggered Strategy and Input Quantization

Distributed Primal-Dual Mirror Dynamics for Constraint-Coupled Optimization

Fixed-time consensus control for uncertain heterogeneous multi-agent systems with high-order dynamics and time-varying delay under generic topologies

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