Predefined-Time Adaptive Fuzzy Bipartite Consensus Control for Multiquadrotors Under Malicious Attacks
Guozeng Cui, Hui Xu, Shengyuan Xu, Juping Gu
Abstract
This article focuses on the predefined-time adaptive fuzzy bipartite consensus control problem for multiquadrotors (MQs) under malicious attacks. The unknown nonlinear dynamics of MQs are effectively identified via the approximation capability of fuzzy logic systems. By integrating the command filter and the error compensation mechanism into the backstepping design procedure, the “explosion of complexity” issue and the effect of filtered error are concurrently eliminated. Additionally, the problem of singularity is skillfully surmounted by the feature of hyperbolic tangent functions and L'Hospital's rule. To deal with unknown malicious attacks, the quadratic-fraction actual controllers for MQs are devised based on the adaptive technique, where the lower bounds of attack signals are not required. It is proven that the closed-loop system is practically predefined-time stable, and the bipartite consensus errors converge into a small neighborhood of the origin within a predefined time. A simulation example is conducted to verify the effectiveness and superiority of the developed predefined-time control strategy.