Research on active vibration and noise control of piezoelectric propeller blades based on the FNNPID-FxLMS algorithm

This study proposed an active control method, namely FNNPID-FxLMS, which combined a fuzzy neural network PID controller with the FxLMS algorithm to address the problem of low-frequency vibration and radiated noise of piezoelectric propeller blades. First, the dynamic characteristics of the blade system were accurately obtained through an offline identification method. A closed-loop hardware-in-the-loop control platform was established to simulate the vibration response of the blades under practical operating conditions. The experimental results showed that, under constant-speed propulsion conditions, the RMS values of vibration were significantly reduced at advance speeds of 6, 12, and 18 knots, while noise reduction at 18 knots was limited. In addition, under multi-line disturbance conditions, the FNNPID-FxLMS algorithm also effectively suppressed vibration and noise, with the maximum reduction in noise RMS reaching 80.3% and the maximum reduction in vibration RMS reaching 52.7%. These results indicated that the FNNPID-FxLMS algorithm exhibited significant advantages in vibration and noise control, including faster convergence speed, lower steady-state error, and stronger robustness. This study provided an effective solution for the active control of propeller vibration and noise in ships and offered support for the application of control technologies in related fields.