Consensus in networked multi-robot systems via local state feedback robust control

Zhang, Shijie; Cao, Yi

doi:10.1177/1729881419893549

Cited by 6 publications

(5 citation statements)

References 33 publications

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“…The parameters are illustrated in Tables 5 and 6 The inverse kinematics is based on Equation (30) to obtain the joint angle, Θ. The change of the new weight value, • ŵi , is obtained according to Equation ( 27) and used to adjust the EE motions according to Equation (28). The learning rate, i.e., η, η 1 , η n,1 , .…”

Section: Synchronous Planning Experiments (1) Collaboration Carryingmentioning

confidence: 99%

“…The cooperative manipulation of robots has been studied a lot. The methods for the cooperative manipulation could be divided into force-based [6][7][8][9] and kinematics-based strategies [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

“…Fractional-order derivative and the uncertain fractional-order differential equations were utilized to predict and correct motion trends, and the rationality of the method is verified by different cases [27]. A state feedback robust controller based on local information was designed to ensure that the states of multiple robots converge to a common motion state [28]. An extended Kalman filter collaborative algorithm based on the error compensation was proposed to reduce the state estimation error of delayed filtering in multi robot systems [29].…”

Section: Introductionmentioning

confidence: 99%

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Real-Time Kinematically Synchronous Planning for Cooperative Manipulation of Multi-Arms Robot Using the Self-Organizing Competitive Neural Network

Zhang

Jin

et al. 2023

Sensors

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This paper presents a real-time kinematically synchronous planning method for the collaborative manipulation of a multi-arms robot with physical coupling based on the self-organizing competitive neural network. This method defines the sub-bases for the configuration of multi-arms to obtain the Jacobian matrix of common degrees of freedom so that the sub-base motion converges along the direction for the total pose error of the end-effectors (EEs). Such a consideration ensures the uniformity of the EE motion before the error converges completely and contributes to the collaborative manipulation of multi-arms. An unsupervised competitive neural network model is raised to adaptively increase the convergence ratio of multi-arms via the online learning of the rules of the inner star. Then, combining with the defined sub-bases, the synchronous planning method is established to achieve the synchronous movement of multi-arms robot rapidly for collaborative manipulation. Theory analysis proves the stability of the multi-arms system via the Lyapunov theory. Various simulations and experiments demonstrate that the proposed kinematically synchronous planning method is feasible and applicable to different symmetric and asymmetric cooperative manipulation tasks for a multi-arms system.

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Section: Synchronous Planning Experiments (1) Collaboration Carryingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Real-Time Kinematically Synchronous Planning for Cooperative Manipulation of Multi-Arms Robot Using the Self-Organizing Competitive Neural Network

Zhang

Jin

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Many researchers have recently studied consensus issues from different perspectives. This is mainly due to their broad application in many fields, including robots [5][6][7][8][9], formations [10][11][12][13], unmanned aerial vehicles [14][15][16][17][18], unmanned surface vehicles [15,[19][20][21], unmanned underwater vehicles [21,22], sensor networks [23,24], etc.…”

Section: Introductionmentioning

confidence: 99%

Modeling of a non-linear multi-agent distributed control system

Tan

Lee

Tai

et al. 2022

JMES

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The goal of our research aims to develop a mathematical model for consensus control system based on Lyapunov Theory and nonlinear dynamics functional equations. This paper describes a new solution that deals with the general-consensus problem and the leader-following consensus problem of non-linear multi-agent system (NMAS) in which the parameters of all follower agents can be different, and with an unforced agent as the leader in the multi-agent system (MAS). Different control rules were constructed for each different follower agent based on its own state variables and its communication with adjacent agents. Finally, numerical simulations are provided to demonstrate the feasibility of the developed mathematical model. The results have demonstrated the designed distributed control system satisfy the Lyapunov Theory since all the agents have converged to its steady state after a period of time.

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“…The distributed agent makes decisions based on the obtained information and its own state in order to achieve the same state for themselves finally [4]. Distributed collaborative control has been extensively researched and applied in many engineering fields, such as automatic generation control [5], unmanned aerial vehicle (UAV) formation flight [6], convergent control of multi-agent [7].…”

Section: Introductionmentioning

confidence: 99%

Research on the Bi-Level Optimization Model of Distribution Network Based on Distributed Cooperative Control

Zhang

Wang

et al. 2021

IEEE Access

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The uncertainty of high-permeability renewable energy output brings about great challenges to the operation control in distribution network. The traditional control mode has lower reliability, higher calculation and greater communication pressure. It is more difficult to realize the technical requirements of ''plug and play'' of power components. Therefore, a bi-level coordinated control model is proposed for the operation and energy management optimization of active distribution network with multi-microgrid in this paper. The consensus algorithm which exists in the multi-agent system is applied in the upper-level model and the capacity utilization ratio of the different microgrids is set as the consistent variable because the ratio of resistance and reactance is usually larger in distribution network and the interests in the different microgrid entities should be distributed fairly. Moreover, in the lower-level model, the lowest operating cost is the final goal and the model predictive control rolling optimization is utilized to reasonably allocate the output of the equipments in the microgrid according to the changing trend of renewable energy. Thereby the tracking of the upper-level control commands is realized. Finally, the simulations are conducted in the IEEE-33 nodes distribution system connected to a multi-microgrid to verify the feasibility and effectiveness of the proposed method, in which a reference for the optimal operation of higher penetration renewable energy to distribution network is provided.INDEX TERMS Bi-level model, consensus algorithm, distributed control, high-permeability, model predictive control. II. CONTROL STRATEGY OF MULTI-MICROGRID SYSTEM A. DISTRIBUTED COLLABORATIVE CONTROL

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Consensus in networked multi-robot systems via local state feedback robust control

Cited by 6 publications

References 33 publications

Real-Time Kinematically Synchronous Planning for Cooperative Manipulation of Multi-Arms Robot Using the Self-Organizing Competitive Neural Network

Real-Time Kinematically Synchronous Planning for Cooperative Manipulation of Multi-Arms Robot Using the Self-Organizing Competitive Neural Network

Modeling of a non-linear multi-agent distributed control system

Research on the Bi-Level Optimization Model of Distribution Network Based on Distributed Cooperative Control

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