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Intelligent-control
- 资料包含三个部分： 1：多智能体系统一致性迭代学习控制的理论和算法 2：运用Hopfield神经网络求解优化问题 3：模糊系统设计的原理和算法-Theory and algorithms of multi-agent system consistency Iterative Learning Control 2:: Data consists of three parts: a use of Hopfield neural networks for solving optimizat
balanced-graph1
- 多智能体一致性实现算法,实现最基本的一致性检测-Simulation for multi-agent consensus problems
multi-agent
- 多智能体算法带时延的一致性验证以及画图，部分内容有注释-Multi-agent algorithm with delay compliance verification and drawing, part of the Notes
ILC-for-multi-agent
- 基于迭代学习控制ILC的多智能体一致性跟踪研究，算法设计-Iterative learning control for multi-agent systems consensus tracking
continuous-time-algorithm
- 多智能体一致性算法，此算法通过交流多个机器人的位置信息，最终实现所有机器人位置的一致。-multi agent consensus algorithm this algorithm can make multi robots to be consensus.
circlenavigation
- 多智能体一致性算法，实现多机器人的共同做圆周运动，同时只需要知道邻居的速度信息-The multi-agent consistency algorithm realizes the multi robot s circular motion, and only needs to know the neighbor s speed information