Hollow core microbubble structures are good candidates for the construction of high performance whispering gallery microresonator and Fabry-Perot (FP) interference devices. In the previous reports, most of interest was just focused on the dual-ended microbubble, but not single-ended microbubble, which could be used for tip sensing or other special areas. The thickness, symmetry and uniformity of the single-ended microbubble in previous reports were far from idealization. Thus, a new ultra-thin single-ended spherical microbubble based on the improved critical-state pressure-assisted arc discharge method was proposed and fabricated firstly in this paper, which was fabricated simply by using a commercial fusion splicer. The improvement to former paper was using weak discharge and releasing pressure gradually during the discharging process. Thus, the negative influence of gravity towards bubble deformation was decreased, and the fabricated microbubble structure had a thin, smooth and uniform surface. By changing the arc discharge parameters and the fiber position, the wall thicknesses of the fabricated microbubble could reach the level of 2 μm or less. The fiber Fabry-Perot (FP) interference technique was also used to analyze the deformation characteristic of microbubble under difference filling pressures. Finding the ends of the microbubbles had a trend of elongation with axial compression when the filling pressure was increasing. Its sensitivity to the inner pressure of microbubble samples was about ~556 nm/MPa, the bubble wall thickness was only of about 2 μm. Besides, a high whispering gallery mode (WGM) quality factor that up to 107 was realized by using this microbubble-based resonator. To explain the upper phenomenon, the microbubble was modeled and simulated with the ANSYS software. Results of this study could be useful for developing new single-ended whispering gallery mode micro-cavity structure, pressure sensors, etc.
Shared control scheme improves the driving performance while having an impact on driver behavior, drivers would constantly adapt their steering behavior mechanism in interaction with a shared controller. This paper proposes a novel data-driven model-based shared control strategy which is capable of considering drivers’ adaptive behaviors in driver-automation interaction to improve safety. The Koopman operator theory, which is a pure data-driven modeling technology, is adopted to yield an explicit control-oriented driver-vehicle model for shared controller design. Besides, a weighted online extended dynamic mode decomposition (WOEDMD) algorithm is proposed to update the Koopman driver model online for better capturing the driver’s adaptive behavior in driver-automation interaction, which settles the problem of driver’s potential behavior mechanism variations in practice. Based on the Koopman driver-vehicle model, a model-based shared controller is proposed in the model predictive control (MPC) framework, and the potential fields are incorporated in the optimization objectives to ensure safety. A group of human-in-the-loop experiments are conducted on a driving simulator to demonstrate the effectiveness of the modeling and shared control methods. The results show that the Koopman operator theory can be exploited for modeling the dynamics of the driver-vehicle integrated system, and the drivers’ adaptive behavior can be captured by the WOEDMD algorithm. Moreover, the shared controller considering the driver’s adaptive behavior improves the driving safety in the collision avoidance task.
Automatic driving has received a broad of attention from academia and industry since it is effective in greatly reducing the severity of potential traffic accidents and achieving the ultimate automobile safety and comfort. This article presents a back-stepping sliding mode controller (BSMC) through linear matrix inequalities (LMIs) for the highly automatic driving vehicle on sloped roads. It includes three key modules, namely, an extended Kalman filter (EKF)-based road slope estimation module, a robust BSMC-LMIs velocity-tracking controller based on the input-output feedback linearization, as well as a longitudinal inverse vehicle dynamics module. The nonlinear combined slip tire model with the transient behavior is introduced to calculate the tire forces properly, which would be further proven to offer more accurate road slope estimations even in a fierce acceleration or deceleration situation. The proposed BSMC-LMIs controller for velocity tracking can handle the lumped uncertainties which include the modeling error, the parameter perturbation, external disturbances, and noises, and guarantee the reachability of the sliding surface, meanwhile, alleviating the chattering phenomenon inherited from the sliding mode structure. Besides, a sufficient condition for the existence of the proposed BSMC is derived by using the LMIs, which ensures the t −𝛼 asymptotical stability on the sliding surface.Finally, the robustness, feasibility, and effectiveness of the proposed BSMC-LMIs controller for velocity-tracking are verified by simulation tests in various working scenarios, which shows satisfying results when dealing with the lumped uncertainties on sloped roads. Moreover, the comparative study also shows that the proposed BSMC-LMIs controller has the best tracking performance when compared to the model predictive control, conventional sliding mode control, and the cubic proportional-integral controller.
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