Practical predefined-time adaptive fuzzy control for quantized nonlinear systems via observer-differentiator scheme

This paper addresses the predefined-time adaptive fuzzy control problem for non-strict feedback nonlinear systems (NSFNS) with input quantization. First, a novel inverse hyperbolic sine state observer was designed based on fuzzy logic to estimate unmeasurable states. Second, owing to the non-smooth and non-differentiable nature of the quantized output signal, a predefined-time differentiator method was proposed to concurrently handle these issues and reduce control signal fluctuations. Theoretical analysis demonstrates that the observer-based output feedback closed-loop system achieves practical predefined-time stability (PPTS): all signals are bounded, and the tracking error converges to a neighborhood of zero within the desired settling time TC, with the observation error suppressed to a negligible bounded region simultaneously. Finally, a simulation example verifies the effectiveness of the proposed scheme.