An Automatic Basic I/O Gain Tuning System Based on Shaping Control Input Histogram for Human-Machine Systems

Abstract

In this study, a fundamental method to tune a basic input/output gain (BIOG) according to usage conditions is proposed for improving work performance in human-machine systems. For improving operability and workability, an I/O gain tuning is effective, but frequent and drastic changes degrade the operability by confusing the machine dynamics. The proposed tuning system adjusts a BIOG at long intervals on the basis of comprehensive features in operator and work content obtained from histogram of control lever input. The target value is set to the normal distribution, meaning that all ranges of the control lever are evenly used in a spring-type lever, as leveling histogram independent of an operator and work content provides the consistent operational feeling, which leads to comfortable operability. To meet practicality and effectiveness, a BIOG curve is set to a polygonal line involving a break point and a saturation point that are tuned by equivalent transform of area differences between the obtained histogram and normal distribution curves. Results of experiments conducted by using a hydraulic arm system showed that the proposed BIOG tuning system improves time efficiency by reducing the area difference while increasing the subjective usability compared with a conventional fixed BIOG system.