Nonsingular sliding mode control method for vibration of driving motor of ship rim propulsion device

Owing to its unique structure, the driving motor of a ship’s rim propulsion device is subject to coupling effects from multiple physical fields. This makes it difficult for conventional control methods to effectively suppress vibrations caused by high-amplitude, complex harmonics, leading to poor speed and torque control performance. Therefore, a vibration suppression method based on disturbance observer combined with non singular sliding mode control is proposed. First, a disturbance observer is constructed to monitor motor torque in real time and accurately capture torque fluctuations induced by vibration. Secondly, design a non singular sliding mode controller to adaptively and quickly adjust the motor speed when vibration is detected. Finally, the quantum particle swarm algorithm, enhanced by the artificial bee colony algorithm, is used to optimize the controller parameters, thereby improving robustness and accuracy under multi-physics field coupling. The experimental results show that this method can accurately observe the motor torque and quickly stabilize the speed between 500 r/min-800 r/min under vibration state, with the smallest torque fluctuation amplitude. This result holds important scientific significance: it validates the effectiveness of nonsingular sliding mode control combined with intelligent optimization algorithms in decoupling multi-physics field interactions and suppressing complex electromagnetic excitation vibrations, offering a new control perspective for understanding motor dynamics under extreme operating conditions. In terms of application value, this method significantly enhances the dynamic response speed and steady-state accuracy of the driving motor, directly improving propulsion efficiency and maneuverability. It also effectively reduces fatigue wear on mechanical components, extends equipment life, and lowers operation and maintenance costs throughout the ship’s life cycle. In the future, we will explore integrating this control strategy with energy efficiency optimization for propulsion devices and investigate predictive vibration suppression methods based on digital twins to achieve smarter, more efficient health management of ship propulsion systems.