Attitude Takeover Control for Noncooperative Space Targets Based on Gaussian Processes with Online Model Learning

One major challenge for autonomous attitude takeover control for on-orbit servicing of spacecraft is that an accurate dynamic motion model of the combined vehicles is highly nonlinear, complex and often costly to identify online, which makes traditional model-based control impractical for this task. To address this issue, a recursive online sparse Gaussian Process (GP)-based learning strategy for attitude takeover control of noncooperative targets with maneuverability is proposed, where the unknown dynamics are online compensated based on the learnt GP model in a semi-feedforward manner. The method enables the continuous use of on-orbit data to successively improve the learnt model during online operation and has reduced computational load compared to standard GP regression. Next to the GP-based feedforward, a feedback controller is proposed that varies its gains based on the predicted model confidence, ensuring robustness of the overall scheme. Moreover, rigorous theoretical proofs of Lyapunov stability and boundedness guarantees of the proposed method-driven closed-loop system are provided in the probabilistic sense. A simulation study based on a high-fidelity simulator is used to show the effectiveness of the proposed strategy and demonstrate its high performance.Comment: 17 pages, 14 figures. Submitted to in IEEE Transactions on Aerospace and Electronic System

Attitude Takeover Control for Noncooperative Space Targets Based on Gaussian Processes with Online Model Learning

One major challenge for autonomous attitude takeover control for on-orbit servicing of spacecraft is that an accurate dynamic motion model of the combined vehicles is highly nonlinear, complex and often costly to identify online, which makes traditional model-based control impractical for this task. To address this issue, a recursive online sparse Gaussian Process (GP)-based learning strategy for attitude takeover control of noncooperative targets with maneuverability is proposed, where the unknown dynamics are online compensated based on the learnt GP model in a semi-feedforward manner. The method enables the continuous use of on-orbit data to successively improve the learnt model during online operation and has reduced computational load compared to standard GP regression. Next to the GP-based feedforward, a feedback controller is proposed that varies its gains based on the predicted model confidence, ensuring robustness of the overall scheme. Moreover, rigorous theoretical proofs of Lyapunov stability and boundedness guarantees of the proposed method-driven closed-loop system are provided in the probabilistic sense. A simulation study based on a high-fidelity simulator is used to show the effectiveness of the proposed strategy and demonstrate its high performance

Holistic resource allocation for multicore real-time systems

This paper presents CaM, a holistic cache and memory bandwidth resource allocation strategy for multicore real-time systems. CaM is designed for partitioned scheduling, where tasks are mapped onto cores, and the shared cache and memory bandwidth resources are partitioned among cores to reduce resource interferences due to concurrent accesses. Based on our extension of LITMUSRT with Intel’s Cache Allocation Technology and MemGuard, we present an experimental evaluation of the relationship between the allocation of cache and memory bandwidth resources and a task’s WCET. Our resource allocation strategy exploits this relationship to map tasks onto cores, and to compute the resource allocation for each core. By grouping tasks with similar characteristics (in terms of resource demands) to the same core, it enables tasks on each core to fully utilize the assigned resources. In addition, based on the tasks’ execution time behaviors with respect to their assigned resources, we can determine a desirable allocation that maximizes schedulability under resource constraints. Extensive evaluations using real-world benchmarks show that CaM offers near optimal schedulability performance while being highly efficient, and that it substantially outperforms existing solutions

Uncertainty in the impact of the COVID-19 pandemic on air quality in Hong Kong, China

Strict social distancing rules are being implemented to stop the spread of COVID-19 pandemic in many cities globally, causing a sudden and extreme change in the transport activities. This offers a unique opportunity to assess the effect of anthropogenic activities on air quality and provides a valuable reference to the policymakers in developing air quality control measures and projecting their effectiveness. In this study, we evaluated the effect of the COVID-19 lockdown on the roadside and ambient air quality in Hong Kong, China, by comparing the air quality monitoring data collected in January-April 2020 with those in 2017-2019. The results showed that the roadside and ambient NO2, PM10, PM2.5, CO and SO2 were generally reduced in 2020 when comparing with the historical data in 2017-2019, while O3 was increased. However, the reductions during COVID-19 period (i.e., February-April) were not always higher than that during pre-COVID-19 period (i.e., January). In addition, there were large seasonal variations in the monthly mean pollutant concentrations in every year. This study implies that one air pollution control measure may not generate obvious immediate improvements in the air quality monitoring data and its effectiveness should be evaluated carefully to eliminate the effect of seasonal variations

Bioinspired Nanoparticulate Medical Glues for Minimally Invasive Tissue Repair

Delivery of tissue glues through small-bore needles or trocars is critical for sealing holes, affixing medical devices, or attaching tissues together during minimally invasive surgeries. Inspired by the granule-packaged glue delivery system of sandcastle worms, a nanoparticulate formulation of a viscous hydrophobic light-activated adhesive based on poly(glycerol sebacate)-acrylate is developed. Negatively charged alginate is used to stabilize the nanoparticulate surface to significantly reduce its viscosity and to maximize injectability through small-bore needles. The nanoparticulate glues can be concentrated to ≈30 w/v% dispersions in water that remain localized following injection. With the trigger of a positively charged polymer (e.g., protamine), the nanoparticulate glues can quickly assemble into a viscous glue that exhibits rheological, mechanical, and adhesive properties resembling the native poly(glycerol sebacate)-acrylate based glues. This platform should be useful to enable the delivery of viscous glues to augment or replace sutures and staples during minimally invasive procedures.United States. National Institutes of Health (GM086433)United States. National Institutes of Health (DE013023

Scalable high-precision trimming of photonic resonances by polymer exposure to energetic beams

Integrated photonic circuits (PICs) have seen an explosion in interest, through to commercialization in the past decade. Most PICs rely on sharp resonances to modulate, steer, and multiplex signals. However, the spectral characteristics of high-quality resonances are highly sensitive to small variations in fabrication and material constants, which limits their applicability. Active tuning mechanisms are commonly employed to account for such deviations, consuming energy and occupying valuable chip real estate. Readily employable, accurate, and highly scalable mechanisms to tailor the modal properties of photonic integrated circuits are urgently required. Here, we present an elegant and powerful solution to achieve this in a scalable manner during the semiconductor fabrication process using existing lithography tools: by exploiting the volume shrinkage exhibited by certain polymers to permanently modulate the waveguide’s effective index. This technique enables broadband and lossless tuning with immediate applicability in wide-ranging applications in optical computing, telecommunications, and free-space optics

A light-reflecting balloon catheter for atraumatic tissue defect repair

A catheter-based technology reflects light to activate a photocurable adhesive for minimally invasive, atraumatic tissue defect closure