Scaled Consensus of Multiagent Systems With Unknown Input Delay and Disturbance

This paper addresses the scaled consensus of multi-agent systems (MAS) with unknown input delays and disturbances. First, a distributed scaled predictive controller framework with disturbance predictive compensation is established for dealing with both unknown input delays and disturbances. Second, an auxiliary loop for unknown disturbance predictive estimation is developed based on delay input predictive transformation technique. Moreover, a disturbance-compensate based distributed predictive control approach and adaptive switching mechanism, which is for matching the value of estimation delay with the one of real input delay, are developed such that the closed-loop MAS achieve the scaled consensus. A simulation example is provided to demonstrate the effectiveness of the proposed method. Note to Practitioners—This work presents a novel control framework for multi-agent systems (MAS) with unknown input delays and disturbances, integrating distributed adaptive delay prediction and disturbance compensation. By introducing a distributed scaled protocol loop and a dirty derivative filter, the proposed approach ensures practical delay estimation and disturbance mitigation. An adaptive switching mechanism combined with Lyapunov stability analysis guarantees the accuracy of delay estimation and enables the MAS to achieve scaled consensus. These contributions provide a robust and practical solution for MAS control in complex environments with uncertain dynamics.