非线性多智能体系统的固定时间分布式优化算法研究  

Fixed-time distributed optimization algorithm for nonlinear multi-agent systems

作　　者：孙庆 杨慧[1] 么娆[1] SUN Qing;YANG Hui;YAO Rao(School of Air Transportation,Shanghai University of Engineering Science,Shanghai 201620,China)

机构地区：[1]上海工程技术大学航空运输学院,上海201620

出　　处：《现代电子技术》2024年第11期105-112,共8页Modern Electronics Technique

基　　金：动态多目标相控阵超声图像束高效同步自适应三维空间定位精度提升机理研究(62171271)。

摘　　要：针对非线性多智能体系统(MASs)的分布式优化问题,提出一种固定时间自适应神经网络输出反馈控制策略。在惩罚函数的基础上,解除一致性约束条件来重构全局目标函数。为了避免反演过程中偏导数的计算和“复杂性爆炸”的问题,设计了一种基于命令滤波的固定时间控制器,并引入补偿信号对滤波误差进行补偿。基于Lyapunov稳定性理论,证明系统中所有输出信号在固定时间内均能达到最优解。最后,通过仿真实验验证了所提控制方案的有效性。A fixed-time adaptive neural network output-feedback control strategy is proposed for the distributed optimization of nonlinear multi-agent systems(MASs).On the basis of the penalty function method,the consensus constraint is removed and the global objective function is reconstructed.To avoid the calculation of partial derivatives and the″complexity explosion″in the backstepping process,a fixed-time controller based on command filtering is designed and the filter errors are compensated by introducing compensating signals.It is proved on the basis of Lyapunov stability theory that all output signals in the system can reach the optimal solution in a fixed time.The simulation results prove the effectiveness of the proposed approach.

关 键 词：多智能体系统 分布式优化 固定时间 命令滤波 自适应反演 自适应神经网络 

分 类 号：TN609-34[电子电信—电路与系统] TP273[自动化与计算机技术—检测技术与自动化装置]