子系统间信息耦合的不确定多智能体系统DMPC

DMPC of an uncertain Multi⁃Agent System with information coupling between subsystems

针对子系统间存在控制输入和系统状态耦合且系统中带有不确定性的多智能体系统(MAS),提出了一种分布式模型预测控制器设计方法。描述了存在不确定性的多智能体系统的平行结构特征,给出了整个系统的约束条件以及子系统间存在的控制输入和系统状态耦合;利用线性矩阵不等式(LMI)方法,将Min-Max优化问题转换为线性规划问题,设计出每个子智能体的模型预测控制器,并可以保证系统稳定性;仿真结果验证了所设计控制方法的有效性。

For Multi⁃Agent Systems(MAS)with uncertainty and coupling of control input and system state between subsystems,a distributed model predictive controller design method is proposed.The parallel structure characteristics of Multi⁃Agent System with uncertainty are described,and the constraints of the whole system and the coupling of control inputs and system states between subsystems are given.The Linear Matrix Inequality(LMI)method is used to transform the Min⁃Max optimization problem into a linear programming problem,and a model predictive controller for each sub⁃agent is designed,and the system stability can be guaranteed.The simulation results verify the effectiveness of the proposed control method.