Periodic event-triggered predictive formation control of networked mobile robots under unknown disturbances

This paper proposes an Extended State Observer (ESO)-based periodic event-triggered predictive formation control algorithm for networked mobile robots under unknown disturbances with system constraints. The aim is to efficiently reduce the computational load and communication burden in the presence of unknown disturbances. First, our approach employs an improved virtual structure method, which divides the formation problem into two subtasks: path-following and formation coordination. Moreover, a periodic event-triggered distributed model predictive control (PETDMPC) strategy is proposed to enhance the implementation of discrete linear systems in computer control systems. This strategy incorporates cooperation constraints related to the parameterized variables in the cost function as coupling terms. Additionally, to reduce the adverse effects of disturbances, a disturbance compensation mechanism based on ESO is incorporated into the periodic event-triggered predictive formation control strategy. Finally, the feasibility of the algorithm and the stability of the closed-loop systems are derived using the discrete Gronwall-Bellman inequality for networked mobile robots under unknown disturbances. Simulation results show the effectiveness of the proposed strategy.