Adaptive Fuzzy Tracking Control With Quantized Prescribed Performance for Nonlinear Systems Under Unknown Disturbances

In this article, the investigation is centered on the problem of fixed-time control within nonlinear systems. A quantized fixed-time prescribed performance control is proposed for the first time, which does not rely on preset thresholds within the performance function. Leveraging the properties of the designed continuous quantizers, the constraint boundaries are dynamically adjusted to ensure that the behavior of the controlled entity remains within a desired narrow range. The challenge of intensive differential computations is bypassed through the adoption of a dynamic surface approach in the backstepping design phase. By seamlessly integrating the principles of backstepping with fuzzy logic systems, an innovative practical fixed-time tracking controller is suggested to address the identified issue. Through a series of simulation examples, the practicality and efficiency of the proposed approach are validated.