State Feedback Control Promotes Transition Efficiency of Bag Filters

How to improve the efficiency of bag filters has attracted a considerable amount of attention. However, effective control of the transition stage, which plays an important role in reducing the time to reach a new steady state, still lacks research. Here, we utilize a nominal linear system with a time delay to characterize the transition stage. We introduce two state feedback mechanisms, namely linear matrix inequality based state-feedback robust controller and parameter-tuning controller based on nonlinear matrix inequality, into control process. Results of both genetic algorithms simulations and closed-loop control experiments show that these controllers dramatically shorten the transition stage compared to open-loop control. Furthermore, we find that parameter-tuning controller outperforms linear matrix inequality based state-feedback robust controller in terms of both stable time and steady error. These results are robust to different experimental settings. From industrial economic perspective, this technology could help to conserve energy and protect environment.