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Summary: This article investigates the issue of orbit coordination control for a class of multi‐spacecraft formation systems in presence of limited communication and external disturbance. To solve the limitation of communication sources, a dynamic event trigger (DET) mechanism is developed to reduce the communication frequency between the follower spacecrafts. Subsequently, we explore a robust DET mechanism‐based distributed self‐learning sliding mode control design, in which a variable learning intensity‐based iterative learning algorithm is designed to approximate and compensate space perturbation. This approach can guarantee an event triggering sequence without Zeno phenomenon and accurate coordination control for formation configuration simultaneously. Compared with the traditional event‐triggered control and other state‐of‐the‐art approaches, the distributed DET control scheme achieves higher control accuracy of formation configuration meanwhile requires less communication resource. Finally, a series of numerical simulations demonstrate the feasibility and superiority of the event triggered control method. [ABSTRACT FROM AUTHOR]

The issue of robust actuator fault reconstruction for a class of Takagi‐Sugeno (T‐S) fuzzy systems with actuator fault and unknown input via a novel Synthesized Learning and Sliding‐Mode Observer (SLSMO) is investigated in this paper. Through a coordinate transformation technique, the considered T‐S fuzzy system is decomposed into two separate subsystems: Subsystem 1 affected only by actuator fault and Subsystem 2 affected by unknown input and actuator fault. In the SLSMO methodology, for Subsystem 1, a new reduced‐order Fuzzy Learning Observer (FLO) is explored to accurately reconstruct actuator fault, while a reduced‐order Fuzzy Sliding Mode Observer (FSMO) is employed for Subsystem 2 such that it has strong robustness against actuator fault and unknown input. Stability and convergence of the fuzzy SLSMO are explicitly proved using Lyapunov's indirect method. The design issue of the reduced‐order FLO and of the reduced‐order FSMO can be uniformly formulated in terms of some Linear Matrix Inequalities (LMIs) that can be directly solved using LMI optimization technique. In addition, a new full‐order FLO is suggested for actuator fault reconstruction in a class of T‐S fuzzy system without unknown input. At the end, a numerical example is applied to verify the effectiveness and superiority of the proposed approaches. [ABSTRACT FROM AUTHOR]

With growing global concern for mainstreaming of environmental protection measures, the promotion of climate change and sustainable development policies, the international community, represented by international organizations, research institutions, and world‐wide businesses, has focused on green finance. Existing research on green finance in the context of environmental trends has been reviewed in terms of the products and determinants of green finance. This study aims to assess the impact of green finance on the decarbonization of economies in the context of a review of current and potential problems and prospects. Based on the examples of the People's Republic of China, the Russian Federation, and the United States of America, the study suggests that today green finance has not yet demonstrated a tangible effect in these countries. Based on the results of the study, it can be argued that in the three countries, the main tool of green finance in the field of decarbonization is green bonds; other types of green finance are used to a limited extent. The progress of the United States and China is not so obvious, but based on the overall involvement of relevant government agencies and businesses in the green bond market, it can be assumed that the results will be observed in the near future. [ABSTRACT FROM AUTHOR]

This study investigates the problem of reconstructing actuator faults for descriptor systems via a PD‐type learning observer. By synthesising the derivatives of the output estimation error into the P‐type learning law, a novel PD‐type learning observer is established to simultaneously reconstruct original system states and actuator faults. Stability analysis of the PD‐type learning observer is explicitly provided. A systematic design method is also suggested based on a linear matrix inequality technique. Further, a robust PD‐type learning observer is designed against process disturbances and measurement noises. At last, a simulation example is used to demonstrate the effectiveness of the proposed fault‐reconstructing method. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper addresses the problem of learning observer (LO)-based fault reconstruction in continuous-time systems. An LO is constructed such that simultaneous reconstruction of system states and actuator faults can be guaranteed. Then, existence conditions of LOs are first introduced to verify whether or not the LOs for fault reconstruction exist. An effective LO-design algorithm is explored such that observer gain matrices can be conveniently solved using linear matrix inequality technique. An extension to sensor-fault reconstruction is also investigated. Finally, two simulation examples are employed to demonstrate the effectiveness of the proposed LO-based fault-reconstructing approaches. [ABSTRACT FROM AUTHOR]

In this study, the problem of robust fault reconstruction in polytopic linear parameter‐varying systems, subject to loss of actuator effectiveness and external disturbances, is investigated using a learning observer (LO). A polytopic LO is proposed to achieve system state estimation and actuator fault reconstruction at the same time. The proposed LO is sensitive to incipient faults because no chattering is induced. Both constant and time‐varying faults can be accurately reconstructed and detected. Moreover, simultaneous fault reconstruction and detection can be performed using a single LO because the reconstructed fault signal can be employed as a fault alarm. The stability and convergence of polytopic LO and the uniformly ultimately boundedness of the dynamic error system is proved using Lyapunov stability theory and H∞ techniques. A systematic design of the LO is effectively solved using standard linear‐matrix‐inequality techniques. At last, simulation results on a satellite system for attitude control verify the effectiveness of the proposed fault‐reconstruction approach. [ABSTRACT FROM AUTHOR]