Research on the automation of many types of construction equipment, including motor graders, is being actively conducted. In a motor grader cabin, the operator has difficulty observing the working environment because of a constructed field of view. Thus, workers rely on their experience and senses. Further, the working environment of the blade must be observed, and a control algorithm should be created to enable autonomous operation. In this study, a blade rotation control strategy considering the soil distribution was proposed. First, a co-simulation environment was constructed using RecurDyn for multibody dynamics analysis and EDEM for discrete element method simulation, and simulations were performed to determine the correlation between soil distribution and the blade rotation angle. Work quality and blade load were analyzed according to the simulation results. The optimal blade rotation angle according to soil distribution was obtained to develop the strategy for autonomous flattening and scattering work. The proposed control strategy was implemented in a 1/4 full-scale motor grader experimental setup. An experiment to evaluate work quality was conducted to validate the effectiveness of the proposed methods. The experimental results indicated that the proposed strategy effectively performed scattering work.

This paper describes a control system for the servo prep column of High-Performance Liquid Chromatography (HPLC) based on fuzzy inference control. The key technology in pharmaceutical and biotechnology industries is refining performance and efforts to reduce costs by purifying target compounds with high purity at high yield while maintaining target compounds, is the major focus of new product development. Among the many refinement techniques, the most popular chromatographic methods require a column that can charge the resin with excellent performance and reproducibility. However, the present HPLC prep column has a hydraulic for control moving stopper and compressed chemical compound. It always causes irregular performances of the column. This paper presents automation control with a servo motor that prevents slurry issues and improves efficiency of the prep column reproducibility and provides easy automation. As an automation method, cortex-m4 as an embedded processor and operating system with LabVIEW, are used to control the HPLC system. To generate the heuristic data for the fuzzy inference control, experiments are conducted to identify correlation between data such as pressure sensor and motor speed. The result will improve performance of the servo prep column of HPLC for automation control based on fuzzy inference control.