执行器饱和的多智能体一致性控制

针对执行器饱和约束下的一类离散多智能体系统，设计了一种基于线性矩阵不等式的一致性控制律，并对线性矩阵不等式解的存在性进行了分析。由于饱和环节的影响，导致多智能体系统的一致性与个体的初始状态有关，不同的控制律所能允许的个体之间的初始偏差的范围不同。为了定量分析控制律所对应的初始偏差范围，引入吸引域的概念对所设计的控制律进行评估，并对控制律参数进行优化以扩大吸引域的范围。最后，通过数值仿真说明了所设计控制律的有效性。

Consensus control for multi-agent systems subject to actuator saturations

Targeting at a class of discrete Multi-Agent Systems (MASs) subject to actuator saturations, a novel consensus controller based on Linear Matrix Inequalities (LMIs) is proposed and the existence of the solution for the LMI is examined. Due to the actuator saturation, the consensus control problem of MASs is related to the initial states of agents. Different controllers may tolerate different ranges of initial states. In order to quantitatively analyze the effects caused by the range of initial states, this paper introduces the concept of Domain of Attraction (DOA) to evaluate the controllers and, subsequently, the controller parameters are optimized to enlarge the DOA. Finally, simulation examples are provided to illustrate the effectiveness of the proposed controller.