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Flocking algorithms essentially consist of three components: alignment, cohesion, and separation. To track a desired trajectory, the flock center should move along the desired trajectory, and thus, the fourth component, navigation, is necessary. The alignment, cohesion, and navigation components are well implemented through consensus protocols and tracking controls, while the separation component...
This paper presents a fuzzy based flocking system. To maintain the distance between agents, we use fuzzy logic controller to design a "force function" which is related to the relative distance between neighbours. And the "force function" is used to control the velocity of agent. To prove the stability of flocking system, we build a Hamilton function which is the kinetic energy...
This paper presents a leader-follower flocking system which is consisted of a group of mobile agents with kinematic model. A "position consensus" algorithm is applied to enable the agents to estimate the flocking central position via neighbor-to-neighbor communication. By using the flocking center position, a cohesion controller is developed to enable the mobile agents to move close with...
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