Consensus Based Formation Control and Trajectory Tracing of Multi-Agent Robot Systems

Wu, Zhengping; Guan, Zhi‐Hong; Wu, Xianyong; Li, Tao

doi:10.1007/s10846-006-9108-7

Cited by 38 publications

(18 citation statements)

References 11 publications

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“…where v r (t) is the reaction rate given in (5). Denoting by v(t) the vector collecting all reaction rates, we may rewrite (7) in matrix form as followsċ(t) = Uv(t) where U is the stoichiometric matrix whose elements are [U] s,r = b r,s − a r,s . That is, modeling the interactions among nodes according to a distributed AC allows fully characterizing the system dynamics through a fluid model in the form of ODEs.…”

Section: B Dynamical Analysis Of Distributed Artificial Chemistrymentioning

confidence: 99%

A Chemistry-Inspired Framework for Achieving Consensus in Wireless Sensor Networks

et al. 2014

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The aim of this paper is to show how simple interaction mechanisms, inspired by chemical systems, can provide the basic tools to design and analyze a mathematical model for achieving consensus in wireless sensor networks, characterized by balanced directed graphs. The convergence and stability of the model are first proven by using new mathematical tools, which are borrowed directly from chemical theory, and then validated by means of simulation results, for different network topologies and number of sensors. The underlying chemical theory is also used to derive simple interaction rules that may account for practical issues, such as the estimation of the number of neighbors and the robustness against perturbations. Finally, the proposed chemical solution is validated under real-world conditions by means of a four-node hardware implementation where the exchange of information among nodes takes place in a distributed manner (with no need for any admission control and synchronism procedure), simply relying on the transmission of a pulse whose rate is proportional to the state of each sensor.

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Section: B Dynamical Analysis Of Distributed Artificial Chemistrymentioning

confidence: 99%

A Chemistry-Inspired Framework for Achieving Consensus in Wireless Sensor Networks

et al. 2014

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“…Consensus problems have attracted increasing attention from researchers studying distributed and decentralized systems in many fields, such as biology, physics, mathematics and control engineering [6,11,12,14,36,41]. Consensus means that all agents in a multi-agent network agree on a common value without recursing to a central coordinator through global communications.…”

Section: Introductionmentioning

confidence: 99%

“…Refs. [2], [8], [15], [17], [26], [41] focused on conditions for asymptotical consensus. In [8], it provides algorithms to make a multi-agent network reach consensus at a point which may be different from the average of the agents' initial states.…”

Section: Introductionmentioning

confidence: 99%

“…Three configurations were discussed: directed networks with fixed topologies, directed networks with switching topologies, undirected networks with communication time delays in fixed topologies. In [41], a general method of controller design for formation keeping and motion trajectory tracing of multi-robot systems was developed and a novel motion model was presented for motion trajectory tracing and group formation control of the multi-robot systems through fixed or changing interactions.…”

Section: Introductionmentioning

confidence: 99%

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Consensus analysis of directed multi-agent networks with singular configurations

Guan

2016

Neurocomputing

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“…In [10], a general method for controller design of formation and trajectory tracking is developed. However, the tracking is not asymptotic and the agent dynamics are single integrators.…”

Section: Introductionmentioning

confidence: 99%

Trajectory tracking and consensus of SISO linear multi-agent systems with formation changes

Lopez-Limon

Cervantes-Herrera

Ruiz-León

et al. 2011

2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control

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In this paper, a decentralized control scheme for group formation and trajectory tracking of multi-agent systems is designed. In this scheme, each agent dynamics is represented by a single-input singleoutput linear system and the information that each controller requires is only the output of the others agents. With the proposed decentralized control law, multiagent system tracks asymptotically the trajectory and formation of the agents, even in the presence of smooth changes of formations. Moreover, the agent dynamics (structure and dimension) are not restricted to be the same, as usually assumed in the literature.A simulation example is provided in order to illustrate the application of the proposed control.

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Consensus Based Formation Control and Trajectory Tracing of Multi-Agent Robot Systems

Cited by 38 publications

References 11 publications

A Chemistry-Inspired Framework for Achieving Consensus in Wireless Sensor Networks

A Chemistry-Inspired Framework for Achieving Consensus in Wireless Sensor Networks

Consensus analysis of directed multi-agent networks with singular configurations

Trajectory tracking and consensus of SISO linear multi-agent systems with formation changes

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