Finite-time distributed optimization formation control of networked robots with time-varying reference signals under directed graphs - Weicheng Zhao; Qian Chen; Li Ding (Discover Artificial Intelligence)
Abstract In this paper, we propose a novel finite-time optimization formation control framework for networked robots, which integrates a finite-time optimal estimator (FOE) with a finite-time local controller (FLC). Within this architecture, each robot is assigned a cost function to ensure optimal performance while minimizing energy consumption. The FOE employs a distributed optimization formation control protocol to compute the optimal positions in finite-time, effectively mitigating the influence of disturbances and uncertainty. The FLC enables the actual position for each robot to track the estimated signal generated by the FOE, thereby achieving coordinated formation control. A Lyapunov-based stability analysis is conducted to derive sufficient conditions ensuring the finite-time convergence and stability of the proposed scheme. Simulation results validate the effectiveness and robustness of the proposed control strategy.