Predefined-Time Control for Multi-Agent Systems With Input Saturation: An Improved Dynamic Surface Control Scheme

Abstract

This paper researches the predefined-time fuzzy adaptive dynamics surface consensus control problem for nonlinear multi-agent systems with input saturation. With regard to nonlinear functions existing in the control systems, fuzzy logic system is employed to estimated them. A novel improved predefined-time dynamics surface filter is designed that can avoid the explosion of complexity problem, and the proposed filter satisfies predefined-time stable simultaneously. With the support of piecewise function, the singularity problem that may exist in virtual controller can be dodged greatly. Furthermore, a ameliorative predefined-time auxiliary dynamic system is presented to cope with input saturation. Combining adaptive backstepping control and predefined-time theory, a predefined-time adaptive fuzzy dynamics surface controller is presented that can assure the systems are predefined-time bounded, though the followers exists in the control saturation. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Numerous actual physical systems and devices can be modeled as uncertain nonlinear MAS. Furthermore, MAS also can be widely applied to disaster relief, spacecraft and multitudinous fields. On the one hand, the practical systems may exist in input saturation phenomenon due to human factors and in most of the relevant literatures, which can affect the system performance or bring about instability. On the other hand, the initial values of actual systems usually cannot be chosen freely because of the influence of environment and other factors. In addition, it is currently ordinarily supposed that realize the stabilization of controlled systems when time approaches infinity. Consequently, a predefined-time adaptive fuzzy controller is presented for MAS with control saturation, which can achieve the predefined-time stabilization of MAS.