Adaptive cooperative control of networked uncalibrated robotic systems with time‐varying communicating delays

Li, Tao; Zhao, Hui; Chang, Y. H.

doi:10.1002/mma.5357

Cited by 5 publications

(3 citation statements)

References 42 publications

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“…As an alternative, a visual servoing scheme ensures a better performance with dynamic objects by combining realtime visual feedback and the actuator control [8]. It makes robots capable of updating objects locations while an endeffector moves toward fruit in real-time [9]. [10] presents a hybrid VS controller combining IBVS and PBVS to control the 3D translation of the camera to guarantee exponential regulation of the robot to a target fruit.…”

Section: Taomentioning

confidence: 99%

Hybrid Visual Servoing Tracking Control of Uncalibrated Robotic Systems for Dynamic Dwarf Culture Orchards Harvest

Li¹,

Qiu²,

Zhao

2020

Preprint

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The paper is concerned with the dynamic tracking problem of SNAP orchards harvesting robots in the presence of multiple uncalibrated model parameters in the application of dwarf culture orchards harvest. A new hybrid visual servoing adaptive tracking controller and three adaptive laws are proposed to guarantee harvesting robots to finish the dynamic harvesting task and the adaption to unknown parameters including camera intrinsic and extrinsic model and robot dynamics. By the Lyapunov theory, asymptotic convergence of the closed-loop system with the proposed control scheme is rigorously proven. Experimental and simulation results have been conducted to verify the performance of the proposed control scheme. The results demonstrate its effectiveness and superiority.

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Section: Taomentioning

confidence: 99%

Hybrid Visual Servoing Tracking Control of Uncalibrated Robotic Systems for Dynamic Dwarf Culture Orchards Harvest

Li¹,

Qiu²,

Zhao

2020

Preprint

Self Cite

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“…During the past decades, the cooperative control problems of multi-agent systems (MASs) have received extensive attention from researchers in different fields [1][2][3], wherein the consensus problem is deemed as one of the most important problems. Recently, a large number of excellent results on consensus problems have emerged [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Bipartite consensus of linear multi‐agent systems with intermittent event‐triggered protocols

Zhao,

Liu,

Wang

2023

Math Methods in App Sciences

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In this paper, bipartite consensus of linear multi‐agent systems with structually balanced signed network is investigated. In particularly, control protocols for consensus are considered to work under an intermittent framework due to some unavoidable factors. Meanwhile, the event‐triggered mechanism is introduced in order to reduce the update frequency of control input. Based on distributed intermittent event‐triggered control, some sufficient conditions are proposed to ensure leaderless and leader‐following bipartite consensus. Moreover, minimum event‐triggered intervals are set to be positive in advance to exclude Zeno behavior. Finally, two numerical examples are provided to verify the effectiveness of theoretical results.

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“…In recent years, the tracking control for multi-agent systems (MASs) has attracted significant research attentions in the control community [1]- [4], due to its wide application background in engineering and scientific fields, such as spacecraft formation flying [5], cooperative control in robotic systems [6], unmanned systems [7], target tracking in sensor networks [8], and so on. Thus, a great of progress has been made on the tracking control of MASs [9]- [12], to name a few.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Adaptive Tracking Control of a Class of Nonlinear Discrete-Time Coupled Multi-Agent Systems With Unknown Dynamics

Zhang

2020

IEEE Access

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This paper studies the trajectory tracking control of a class of multi-agent systems, in which, each agent is expressed by a nonlinear discrete-time unknown dynamics and can interact with its neighbors via the history outputs of its neighbors. In order to tackle each unknown dynamics, based on its neighbors' and its own history I/O data and neural network, an approximate model is established by the direct data-driven method. Using the neighbors' history information and the reference trajectory, the decentralized adaptive indirect data-driven control is designed; then, the feedback gain matrix online is designed and adjusted by measured output data and previous estimates. For each agent, this is an adaptive control process of prediction, estimation, and adjustment, which needs to solve some nonlinear optimization problems online, can surmount the negative effects of the modeling errors caused by neural networks, and is the key to making each agent output asymptotically track the given reference trajectory. The convergence analysis shows that the applied method is effective and feasible. INDEX TERMS Multi-agent system, tracking control, indirect data-driven method, adaptive control, nonlinear discrete-time system.

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Adaptive cooperative control of networked uncalibrated robotic systems with time‐varying communicating delays

Cited by 5 publications

References 42 publications

Hybrid Visual Servoing Tracking Control of Uncalibrated Robotic Systems for Dynamic Dwarf Culture Orchards Harvest

Hybrid Visual Servoing Tracking Control of Uncalibrated Robotic Systems for Dynamic Dwarf Culture Orchards Harvest

Bipartite consensus of linear multi‐agent systems with intermittent event‐triggered protocols

Decentralized Adaptive Tracking Control of a Class of Nonlinear Discrete-Time Coupled Multi-Agent Systems With Unknown Dynamics

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