Privacy-Preserving Adaptive Tracking Control for Multiagent Systems

Siyu Guo

TL;DR: This paper investigates the problem of tracking control for multi-agent systems.

Abstract: This paper investigates the privacy-preserving adaptive tracking control problem for nonlinear multiagent systems with unknown disturbances. Firstly, based on the phenomenon of Lorenz system, a masking function endowed with uncertainty and unpredictability is proposed. Meanwhile, a time-assist function is designed to achieve privacy protection within a predefined period of time, which enhances the flexibility of the mechanism. In addition, a dynamically self-adjustable gain parameter is designed in the disturbance observer. The introduction of this parameter enables the proposed disturbance observer to not only handle unknown disturbances but also achieve better results in improving system performance. Afterward, the Lyapunov stability theorem is utilized to prove that all signals of the closed-loop system are semi-globally uniformly ultimately bounded. Finally, simulation results confirm the effectiveness of the proposed control scheme.

Submission Number: 188