基于自适应滑模的不确定Euler-Lagrange多智能体系统抗扰动蜂拥控制

针对具有参数不确定性和未知外部扰动的Euler-Lagrange多智能体系统,设计一种基于自适应滑模控制的分布式蜂拥算法.该算法使用自适应滑模控制和自适应控制律分别补偿未知的外部扰动与模型中可线性参数化回归的不确定项,从而在实现蜂拥控制的同时,避免智能体对外部扰动先验知识的要求.理论分析表明,在多智能体达成蜂拥的同时,算法保证滑模的自适应增益有界.此外,所提出的算法同时考虑虚拟领导者追踪与基于目标区域的跟踪问题,并给出碰撞避免的条件.最后,通过算例仿真验证所提出算法的有效性.

Adaptive sliding mode control based flocking control of uncertain Euler-Lagrange multi-agent systems subject to unknown external disturbances

This paper addresses the distributed flocking control problem based on adaptive sliding mode control for a networked uncertain Euler-Lagrange(EL) system with parameter uncertainties and unknown external disturbances. The proposed algorithm uses both adaptive sliding mode control(SMC) and adaptive control law to compensate for the unknown external disturbances and linear parameterizable uncertainty terms, respectively, thus avoiding the requirement of prior knowledge of the external disturbances. Theoretical analysis shows that the adaptive gains employed in the algorithm remain bounded while the agents achieve the desired collective flocking behavior. In addition, the proposed algorithm considers both leader tracking control and the region control, and gives the condition for collision avoidance. Finally, numerical simulations verify the theoretical results of the proposed algorithm.