In the paper, we study the swarm control problem for a high-order self-organized system with unknown nonlinear dynamics and unmeasured states. In previous work, swarm control, which can change the distance between agents when swarm moves, is discussed. However, in practical applications, the high-order states of agents are not easy to be measured, and the unknown nonlinear dynamics in the system are also not conducive to the efficient and reliable operation of the system. To solve the problem that the high-order states of agents are not available when designing the controller, a high-gain state observer is designed to estimate those unmeasurable states. And to overcome the negative impact of unknown nonlinear dynamics on system performance, the fuzzy logic system is introduced to approximate the unknown nonlinear dynamics. Based on the sliding mode control theory, we design a distributed fuzzy adaptive swarm controller. And the stability of the proposed controller is proved. Finally, the self-organized system based on mecanum wheeled omnidirectional vehicles is taken as an example for numerical simulation, and the simulation results show that the proposed fuzzy adaptive swarm control law is effective.

在本文中，我们研究了具有未知非线性动力学和未测量状态的高阶自组织系统的群控制问题。在之前的工作中，讨论了群体控制，它可以在群体移动时改变代理之间的距离。然而，在实际应用中，代理的高阶状态不易测量，系统中未知的非线性动力学也不利于系统的高效可靠运行。为了解决在设计控制器时智能体的高阶状态不可用的问题，设计了一个高增益状态观察器来估计那些不可测量的状态。并且为了克服未知非线性动力学对系统性能的负面影响，引入模糊逻辑系统来逼近未知非线性动力学。基于滑模控制理论，我们设计了一种分布式模糊自适应群控制器。并证明了所提出控制器的稳定性。最后，以基于麦克纳姆轮式全向车的自组织系统为例进行了数值仿真，仿真结果表明所提出的模糊自适应群控制律是有效的。