Data-Driven Feedforward Control for Trade-Off Optimization in Machine Stand Vibration Systems

In various industrial mechatronic equipment for processing and assembling electronic components, high-acceleration drives in the internal positioning mechanisms cause machine stand vibrations, degrading their production accuracy and throughput. Generally, a trade-off exists between the fast and precise control of positioning mechanisms and suppressing machine stand vibrations, which complicates control design. This study presents an extended data-driven vibration suppression feedforward (FF) control method that addresses both positioning performance and machine stand vibrations. The proposed method designs FF controllers to pursue the trade-off through a multi-objective optimization problem using predicted responses of both the positioning device and the machine stand. Experiments with a laboratory table positioning system demonstrate the effectiveness of the proposed method, compared to an existing data-driven vibration suppression FF control method.