Adaptive Neural Network-Based Event-Triggered Control for Finite-Time Consensus in Second-Order Multi-Agent Systems with Unknown Nonlinear Dynamics
摘要
The finite-time consensus control is investigated for second-order nonlinear multi-agent systems with unknown nonlinear dynamics. Utilizing an event-triggered adaptive neural network control strategy, control protocals are proposed via Lyapunov stability theory and backstepping technique. Sufficient condition is established for achieving leader-follower consensus. Finally, simulation results demonstrate the effectiveness of the proposed theoretical approach.