多智能体系统协同互估计与控制一体化框架

Although cooperative control of multi-agent systems has been extensively studied, existing distributed control algorithms still suffer the problem of performance degradation when individual sensor failure occurs. This paper proposes a novel integrated design framework for cooperative mutual estimation and control, which enhances the resilience of multi-agent system cooperative control by fully leveraging the measurement information of other agents from individual sensors. Firstly, a distributed sensing network model is constructed for the overall multiagent systems. Secondly, based on the predefined cooperative control task, each individual establishes a predictive estimate of the global control input; A distributed consensus-based tracking estimator is further designed for reconstructing the global measurement output. Then, a local observer is designed to estimate the overall state using both the global control input prediction and the global measurement output tracking. Furthermore, the proposed integrated design framework is applied to the cooperative consensus control problem of linear multi-agent systems, and a joint design method for the feedback gains is introduced. Theoretical analysis verifies the effectiveness of the proposed framework. Simulation results further demonstrate that the framework is capable of performing cooperative control tasks of multi-agent systems even in the presence of partial sensor failure. Finally, potential directions for future research on integrated framework of cooperative mutual estimation and control are discussed.