Formation control of multiple nonholonomic mobile robots with limited information of a desired trajectory

Wang, Jing; Obeng, Morrison; Yang, Tianyu; Staskevich, Gennady; Abbe, Brian

doi:10.1109/eit.2014.6871823

Cited by 12 publications

(2 citation statements)

References 29 publications

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“…Figure 4 shows the trajectories of the agents when the control ( 19) is applied and the communications are triggered according to the CTC of Theorem 1. Figure 4 (a) illustrates the results obtained using the accurate estimator (21), Figure 4(b) illustrates results obtained using the simple estimator (38). The agents converge to the desired formation with a limited number of communications, even in presence of perturbations.…”

Section: Formation Control With Ship Dynamical Modelmentioning

confidence: 99%

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Distributed event-triggered control strategies for multi-agent formation stabilization and tracking

et al. 2019

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This paper addresses the problem of formation control and tracking a of desired trajectory by an Euler-Lagrange multi-agent systems. It is inspired by recent results by Qingkai et al. and adopts an event-triggered control strategy to reduce the number of communications between agents. For that purpose, to evaluate its control input, each agent maintains estimators of the states of its neighbour agents. Communication is triggered when the discrepancy between the actual state of an agent and the corresponding estimate reaches some threshold. The impact of additive state perturbations on the formation control is studied. A condition for the convergence of the multi-agent system to a stable formation is studied. The time interval between two consecutive communications by the same agent is shown to be strictly positive. Simulations show the effectiveness of the proposed approach.Distributed cooperative control of a multi-agent system (MAS) usually requires significant exchange of information between agents. In early contributions, see, e.g., [25,39], communication was considered permanent. Recently, more practical approaches have been proposed. For example, in [40,41,42], communication is intermittent, alternating phases of permanent communication and of absence of communication. Alternatively, communication may only occur at discrete time instants, either periodically as in [13], or triggered by some event, as in [9,11,46,37]. This paper proposes a strategy to reduce the number of communications for displacement-based formation control while following a desired reference trajectory. Agent dynamics are described by Euler-Lagrange models and include perturbations. This work extends results presented in [44] by introducing an event-triggered strategy, and results of [19,33,34] by addressing systems with more complex dynamics than a simple integrator. To obtain efficient distributed control laws, each agent uses an estimator of the state of the other agents. The proposed distributed communication triggering condition (CTC) involves the inter-agent displacements and the relative discrepancy between actual and estimated agent states. A single a priori trajectory has to be evaluated to follow the desired path. Effect of state perturbations on the formation and on the communications are analyzed. Conditions for the Lyapunov stability of the MAS have been introduced. The time interval between two consecutive communications by the same agent is shown to be strictly positive.This paper is organized as follows. Related work is detailed in Section 2. Some assumptions are introduced in Section 3 and the formation parametrization is described in Section 4. As the problem considered here is to drive a formation of agents along a desired reference trajectory, the designed distributed control law consists of two parts. The first part (see Section 4) drives the agents to some target formation and maintains the formation, despite the presence of perturbations. It is based on estimates of the states of the agents described in Section 5.1...

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Section: Formation Control With Ship Dynamical Modelmentioning

confidence: 99%

“…This requires a good synchronization among agents of the state of the virtual leader. Virtual structures have been introduced in [27,38], where the agent control is designed to satisfy constraints between neighbours. Such approaches also address the problem of leader failure.…”

Section: Related Workmentioning

confidence: 99%