Hybrid active-passive micro-vibration isolation for precision equipment using adaptive-network-based fuzzy inference system

Abstract

Conventional vibration isolation techniques fail to meet stringent VC-D and VC-E level requirements specified in Vibration Criteria for precision equipment micro-vibration control. To achieve higher control levels for precision equipment, this study introduces an intelligent control strategy using adaptive-network-based fuzzy inference system (ANFIS) for a hybrid vibration isolation system that combines passive rubber elements with active piezoelectric actuators. A binary control method is first developed to analyze the effects of key control parameters, and the results are used to construct fuzzy membership functions for the ANFIS model. Experiments are implemented to validate the simulation methods and analyze the control effects under various conditions. Results show conventional passive isolation achieves only VC-C level, while the hybrid system attains higher vibration control accuracy with minimal active force through appropriate parameters. The developed ANFIS-based adaptive isolation system demonstrates superior control performance and reliability compared to uncontrolled binary isolation system.