Attitude Control of Airbag Isolation System Based on Adaptive Model Predictive Control

The air bag vibration isolation device has an important application in ship vibration and noise reduction. However, traditional fuzzy control has problems such as slow response and low accuracy when dealing with complex environments and multi-variable coupling. In this paper, a new method based on Adaptive Model Predictive Control (AMPC) is proposed to improve the attitude control performance of the airbag isolation system. Firstly, the system is modeled and a discrete-time state space model is established. By dynamically adjusting the model parameters, the future state of the system is accurately predicted. Then, a rolling optimization MPC controller was designed to select the optimal airbag for inflating and deflating operations by using the real-time collected pressure and displacement data, so as to realize the precise control of the attitude. Experimental results show that compared with the traditional fuzzy control method, the control algorithm based on AMPC shows significant advantages in control accuracy, response speed and pressure balance. This study provides a new technical approach for the efficient control of the air bag vibration isolation system, and lays a foundation for the application of more complex ship vibration and noise reduction system in the future.