A self-tuning PID (Proportion-Integral-Derivative) control method based on the adaptive mechanism was proposed for the magnetic suspension active vibration isolation system with the characteristics of nonlinear, time-varying, and model parameter uncertainty. The controller identified the controlled object parameters online and solved the controller parameters in real time. To test the effectiveness of the proposed method, a six degree-of-freedom (DOF) magnetic suspension active vibration isolation system was designed and built. The six DOF dynamic model of the vibration isolation system with uncertain model parameters was derived for control. Experiments were carried out and compared with the control effects of the tradition PID control and cascade PID control algorithm. The experimental results show that the proposed self-tuning PID controller has more outstanding practicality and effectiveness in solving the model parameter uncertainty problem compared with the existing studies at home and abroad, and it also proves that the control method has a good isolation effect on the wide band disturbances.

In this study, the topology-optimized solid-lattice hybrid structures with variable-density or iso-density are proposed to achieve the structural lightweight and performance requirements. Based on ...

We introduce a circle rolling method (CRM) for boundary extraction from 2D point clouds. The core idea is to create a circle that performs pure rolling on the perimeter of the point cloud to obtain the boundary. For a 3D point cloud, a plane adsorbs points on both sides to create a 2D point cloud, and the CRM is used to extract the boundary points and map them back into space to obtain 3D boundary points. Continuously moving this plane can obtain a complete boundary, which is called the moving adsorption rolling method (MARM). In this paper, we solve the interference problems in our method caused by unidirectional overlapping points and porous structures and successfully validate the solutions in practical examples. Our point cloud boundary extraction method is faster in 2D and better for surface concavities extracted in 3D compared to existing methods, and it is unaffected by sparse points within the point cloud.