Disturbance observer-based adaptive fuzzy finite-time consensus control of uncertain fractional-order multi-agent systems with input quantization

Finite-time consensus control of fractional-order multi-agent systems is a challenging subject, particularly in the presence of input quantization and external disturbances. This paper proposes an adaptive fuzzy finite-time consensus control method for a class of uncertain fractional-order multi-agent systems with input quantization and unknown disturbances. Considering the condition that Input signals in practical applications cannot always remain linearly continuous, an input quantizer is introduced, which contains a linear part and a disturbance part, to reduce the communication burden. A disturbance observer is designed to simultaneously approximate unknown terms, with consistent approximation errors in the fuzzy logic system, external unknown disturbances, and disturbance terms in the input quantizer. Furthermore, by using a fractional-order dynamic surface filter, the problem of “explosion of terms” in the adaptive backstepping method is avoided. Theoretical analysis demonstrates that even with the coexistence of external unknown disturbance terms and input quantization, the proposed method can ensure that the internal signals of the entire closed-loop system are uniformly bounded, and the consensus error gradually converges within a small neighborhood of the origin in a finite time. Finally, a numerical simulation experiment verifies the reliability of the proposed method.