Type-2 fuzzy logic framework for adaptive noise control in vibrating structures

Active noise control (ANC) in vibrating structures often suffers performance degradation under uncertain excitation and parameter drift. This study introduces an interval Type-2 fuzzy logic controller (IT2 FLC) for adaptive ANC in multi-mode systems, explicitly modelling “uncertainty about uncertainty” via a footprint of uncertainty in the fuzzy rule base. A two-degree-of-freedom mass–spring–damper model is used to represent structural dynamics, and both broadband and tonal disturbances are simulated. The IT2 FLC adapts its membership-function bounds online based on error variance, yielding a robust control law that compensates for up to ±25% drift in mass and stiffness. Controller performance is evaluated in MATLAB/Simulink and on a dSPACE DS1104 rapid-prototyping platform interfaced with a physical beam rig. Compared to classical ANC methods such as least-mean-square filtering and H∞ control, as well as Type-1 fuzzy logic, the proposed interval Type-2 fuzzy logic controller (IT2 FLC) consistently demonstrates superior performance. It achieves up to 28 dB broadband attenuation under nominal conditions and sustains over 23 dB even under ±25% structural parameter drift, significantly outperforming other benchmarks. The controller exhibits fast convergence (≤ 0.35 s) and maintains real-time feasibility with ≤ 25% CPU utilization at a 1 kHz update rate on standard DSP hardware. A hardware-in-the-loop implementation on a physical cantilever beam rig confirms robustness and stability. These results validate the IT2 FLC as a computationally efficient, highly adaptive, and cost-effective solution for industrial noise control applications in uncertain environments.