Robust Control of a System with a Pneumatic Spring

Abstract: Recently, series elasticity has been realized using pneumatics in human-robot interaction systems. Pneumatic circuits provide not only a flexible power transmission, but also the elastic element in a series elastic actuator (SEA). Pneumatic series elastic systems involve more than twice the number of parameters that influence system behaviors in comparison with rigid robotic systems. In this study, a position controller is proposed for pneumatic SEA systems that eliminates the need of identifying a system model by employing the time delay estimation (TDE) technique. The TDE technique is effective in compensating for system dynamics and all uncertainties involved in system behaviors without imposing computation load. TDE error is cancelled out through an adaptive way, which improves control performance and leads to asymptotic stability. A simulation study demonstrates the robustness of the proposed controllers against uncertainties imposed on the motor system as well as uncertainties on the end-effector. It shows the efficacy of the adaptive compensation for TDE error

Impact of Location Spoofing Attacks on Performance Prediction in Mobile Networks

Performance prediction in wireless mobile networks is essential for diverse purposes in network management and operation. Particularly, the position of mobile devices is crucial to estimating the performance in the mobile communication setting. With its importance, this paper investigates mobile communication performance based on the coordinate information of mobile devices. We analyze a recent 5G data collection and examine the feasibility of location-based performance prediction. As location information is key to performance prediction, the basic assumption of making a relevant prediction is the correctness of the coordinate information of devices given. With its criticality, this paper also investigates the impact of position falsification on the ML-based performance predictor, which reveals the significant degradation of the prediction performance under such attacks, suggesting the need for effective defense mechanisms against location spoofing threats

Acetyl-CoA-mediated autoacetylation of fatty acid synthase as a metabolic switch of de novo lipogenesis in Drosophila

De novo lipogenesis is a highly regulated metabolic process, which is known to be activated through transcriptional regulation of lipogenic genes, including fatty acid synthase (FASN). Unexpectedly, we find that the expression of FASN protein remains unchanged durin