Near-optimal sliding mode control for multi-robot consensus under dynamic events

Abstract

We propose a continuous-time design for finite-time consensus control for multi-robot system using event-based near-optimal sliding mode control. The system has a leader–follower framework prone to external bounded disturbance. The proposed design comprises of three parts: (i) formulation of control-affine dynamics, (ii) design a triggering condition for control updates that guarantee stability and consensus in the system, and (iii) design a near-optimal sliding mode control using neural-network based approximate dynamic programming. We derive a bound on inter-event time that guarantees admissibility of updated control input values. We finally validate the efficacy of proposed design through real-time experiments using three Pioneer P3-DX mobile robots (leader and two followers) and comparative analyses with other state-of-the-art approaches. The control updates of follower-1 and follower-2 robots are approximately 30.00% and 32.22%, respectively, that reduce the computational burden in multi-robot framework.