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This paper presents an admittance controller based on the passivity theory for a powered upper-limb exoskeleton robot which is governed by the nonlinear equation of motion. Passivity allows us to include a human operator and environmental interaction in the control loop. The robot interacts with the human operator via F/T sensor and interacts with the environment mainly via end-effectors. Although the environmental interaction cannot be detected by any sensors (hence unknown), passivity allows us to have natural interaction. An analysis shows that the behavior of the actual system mimics that of a nominal model as the control gain goes to infinity, which implies that the proposed approach is an admittance controller. However, because the control gain cannot grow infinitely in practice, the performance limitation according to the achievable control gain is also analyzed. The result of this analysis indicates that the performance in the sense of infinite norm increases linearly with the control gain. In the experiments, the proposed properties were verified using 1 degree-of-freedom testbench, and an actual powered upper-limb exoskeleton was used to lift and maneuver the unknown payload.

Handling heavy-load materials is the most common operation in iron and steel making processes. There are numerous operations in which workers directly deal with heavy loads without equipment. The refractory constructions in the converter and AOD (Argon Oxygen Decarburization) furnaces are representative examples. Transferring thousands of heavy materials repeatedly over a long period of time can not only cause musculoskeletal diseases, which occur 70% on the waist and 30% on other parts such as wrists, elbows, shoulders, etc. but also contain latent risks of safety accidents.In this paper, a novel stand-alone powered exoskeleton robot suit was developed for assisting the strength of waist, lower back, and hip joints that are physically vulnerable during handling heavy-load materials. The simple robot structure reduces the frame weight as well enabling easy motion control. The robot is capable of moving freely due to the stand-alone actuators. The developed novel clutch system generates a smooth transition against various working conditions. This technology significantly diminishes the physical fatigue of operators and will subsequently prevent further muscular skeletal disorders as well as safety accidents.

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Electrospinning, one of the most effective ways of producing nanofibers, has been applied in as many fields throughout its long history. Starting with far-field electrospinning (FFES) and advancing to the near-field, the application area has continued to expand, but lack of understanding of the exact jet speed and fiber deposition rate is a major obstacle to entry into precision micro- to nano-scale manufacturing. In this paper, we, for the first time, analyze and predict the jet velocity and deposition rate in near-field electrospinning (NFES) through novel image analysis process. Especially, analog image is converted into a digital image, and then, the area occupied by the deposited fiber is converted into a velocity, through which the accuracy of the proposed method is proved to be comparable to direct jet speed measurement. Finally, we verified the proposed method can be applied to various process conditions without performing delicate experiments. This research not only will broaden the understanding of jet speed and fiber deposition rate in NFES but also will be applicable to various areas including patterning of the sensor, a uniform arrangement of nanofibers, energy harvester, reinforcing of composite, and reproducing of artificial tissue.