Figure 5 - available via license: Creative Commons Attribution 4.0 International
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Position of agents in the Cartesian coordinate system for a square formation. Gray symbols indicate the initial positions and the black symbols represent the final positions of the agents.
Source publication
An LQR-based Control design and gain tuning strategies proposals for a multi-agent system are presented in this article, the agents are connected in an undirected graph. Controller gains tuning are adjusted by selecting the Q and R weighting matrices of the Linear Quadratic Regulator. Agreement (consensus) is one of the fundamental problems in mult...
Contexts in source publication
Context 1
... the simulation, the initial states of the multi-agent system were considered as uniformly distributed random variables. Thus, the agents must leave their position and maintain a given desired formation and the response of the system is illustrated in Figure 5. The Figure 5 illustrates the formation of a multi-agent system, where Ag1, Ag2, Ag3, and Ag4 represent the dynamics of agents 1, 2, 3, and 4, respectively. ...
Context 2
... the agents must leave their position and maintain a given desired formation and the response of the system is illustrated in Figure 5. The Figure 5 illustrates the formation of a multi-agent system, where Ag1, Ag2, Ag3, and Ag4 represent the dynamics of agents 1, 2, 3, and 4, respectively. Also, in this figure, it is noted that the agents move in space at a constant speed because the vehicles have an initial velocity different from zero; thus, during the training process the velocity is kept constant. ...
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