Model-Free Safe Adaptive Synchronization Control of Nonlinear Multi-Agent Systems

Huijuan Li, Nan Gu, Dan Wang, Zhouhua Peng

TL;DR: Model-Free safe adaptive synchronization control of nonlinear multi-agent systems

Abstract: This paper investigates the model-free safe adaptive synchronization problem for high-order nonlinear multi-agent systems with completely unknown internal uncertainties, unknown external disturbances, and unknown control input gains. A safe adaptive synchronization controller is proposed based on a finite-time data-driven fuzzy predictor and an input-to-state safe control barrier function (ISSs-CBF). Specifically, by utilizing the integral of historical data, a finite-time data-driven fuzzy predictor is designed to estimate the unknown model parameters and ensure the convergence of the estimation without requiring persistent excitation. Based on this estimated information, a safe adaptive synchronization controller is proposed, which allows the tasks of leader-following synchronization and safety to be represented separately but can be implemented jointly. The closed-loop control system is proven to be input-to-state stable via Lyapunov theory. Moreover, the multi-agent systems are proven to be input-to-state safe. Simulation results validate the effectiveness of the proposed model-free safe adaptive synchronization control method for high-order nonlinear multi-agent systems with a fully unknown dynamic model.

Submission Number: 140