Data-driven safe gain-scheduling control

Data-based safe gain-scheduling controllers are presented for discrete-time linear parameter-varying systems (LPV) with polytopic models. First, $\lambda$-contractivity conditions are provided under which the safety and stability of the LPV systems are unified through Minkowski functions of the safe sets. Then, a data-based representation of the closed-loop LPV system is provided, which requires less restrictive data richness conditions than identifying the system dynamics. This sample-efficient closed-loop data-based representation is leveraged to design data-driven gain-scheduling controllers that guarantee $\lambda$-contractivity and, thus, invariance of the safe sets. It is also shown that the problem of designing a data-driven gain-scheduling controller for a polyhedral (ellipsoidal) safe set amounts to a linear program (a semi-definite program). The motivation behind direct learning of a safe controller is that identifying an LPV system requires satisfying the persistence of the excitation (PE) condition. It is shown in this paper, however, that directly learning a safe controller and bypassing the system identification can be achieved without satisfying the PE condition. This data-richness reduction is of vital importance, especially for LPV systems that are open-loop unstable, and collecting rich samples to satisfy the PE condition can jeopardize their safety. A simulation example is provided to show the effectiveness of the presented approach.     

Novel Movable Typing for Personalized Vein-Chips in Large Scale: Recapitulate Patient-Specific Virchow's Triad and its Contribution to Cerebral Venous Sinus Thrombosis

The Vein-Chip recapitulates CVST Virchow's triad and enables systematic characterization of venous thrombogenesis with respect to fibrin formation and platelet aggregation. Distinct from the arterial setting, platelets universally adhere across the entire CVS Vein-Chip independent of stenotic geometry and flow disturbance. Intriguingly, fibrin propagates along with the flow direction, but exclusively deposits to the inner vessel wall. Upon inflammatory endothelial injury, fibrin deposition mirrors to the outer vessel wall, but still not in the lumen. Together, the Vein-Chip promises future applications for personalized thrombotic assessment and monitoring.     

Cooperative Relay Networks Based on the OAM Technique for 5G Applications

Orbital Angular Momentum (OAM) is an intrinsic property of electromagnetic waves. Great research has been witnessed in the last decades aiming at exploiting the OAM wave property in different areas in radio and optics. One promising area of particular interest is to enhance the efficiency of the available communications spectrum. However, adopting OAM-based solutions is not priceless as these suffer from wave divergence especially when the OAM order is high. This shall limit the practical communications distance, especially in the radio regime. In this paper, we propose a cooperative OAM relaying system consisting of a source, relay, and destination. Relays help the source to transmit packets to the destination by providing an alternative connection between source and destination. This cooperative solution aims on the one hand, through best-path selection, on increasing the communications range. On the other hand, through the parallel transmission orders allowed by OAM carrying waves, the system could raise its total transmission throughput. Simulation results show that combining a cooperative relay with OAM improves the system throughput compared to using each element separately. In addition, the proposed cooperative relaying OAM outperforms the cooperative relaying non-orthogonal multiple access scheme, which is a key spectrally efficient technique used in 5G technology.