Active debris removal (ADR) is positioned by space agencies as an in-orbit task of great importance for stabilizing the exponential growth of space debris. Most of the already developed capturing systems are designed for large specific cooperative satellites, which leads to expensive one-to-one solutions. This paper proposed a versatile hybrid-compliant mechanism to target a vast range of small uncooperative space debris in low Earth orbit (LEO), enabling a profitable one-to-many solution. The system is custom-built to fit into a CubeSat. It incorporates active (with linear actuators and impedance controller) and passive (with revolute joints) compliance to dissipate the impact energy, ensure sufficient contact time, and successfully help capture a broader range of space debris. A simulation study was conducted to evaluate and validate the necessity of integrating hybrid compliance into the ADR system. This study found the relationships among the debris mass, the system’s stiffness, and the contact time and provided the required data for tuning the impedance controller (IC) gains. This study also demonstrated the importance of hybrid compliance to guarantee the safe and reliable capture of a broader range of space debris.

No abstract

We demonstrate an adaptive polarization control system of a 10.2 W non-polarization-maintaining fiber amplifier based on stochastic parallel gradient decent (SPGD) algorithm. The experimental investigation shows that the system can used to compensate for the polarization fluctuation of the fiber amplifier effectively and perform well over a long-time observation. When the adaptive polarization control system is in closed loop, the extinction ratio increases from 2.28 dB to 11.54 dB, and more than 93.4% of the total power in desired polarization direction is achieved.

Carbon trading is an effective measure for the road transportation to reduce energy consumption and carbon emissions. Carbon emission quotas are the primary concern to ensuring the efficiency of carbon trading. However, the existing studies have mostly focused on carbon emission quotas in different regions, i.e., countries and provinces. Few literature studies simulate carbon quota allocation in the road transportation. A novel approach from the perspective of carbon emission intensity of vehicle is proposed, on the basis of data envelopment analysis (DEA) model. Unlike other studies, the idea of allocation of baseline excitation is introduced and the intensity is included in the model as the baseline. Firstly, the Delphi method is employed to select input and output indicators. Secondly, carbon emission intensity is determined by the cumulative distribution function (CDF). Furthermore, the carbon emission quotas in road transportation in 30 provinces of China are used to validate the model. The results show that (1) the carbon emission intensity of commercial trucks and buses in China’s road transport industry is 75.04 g/t·km and 13.12 g/p·km, respectively; (2) the provinces of Shanghai, Guangdong, and Xinjiang have the greatest carbon reduction potential and Henan, Hunan, and Anhui have the largest increase in emission quotas; (3) compared with traditional “history responsibility” and “baseline” methods, the proposed approach increases allocation efficiency by 19% and 14%, respectively; and (4) the approach can make the carbon emission quotas play the role of incentive while taking fairness into account and can more effectively promote the implementation of carbon trading system in road transportation.