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In the post-capture stage, the tumbling target rotates the combined spacecraft system, and the detumbling operation performed by the space robot is required. To save the costly onboard fuel of the space robot, this paper aims to present a novel post-capture detumbling strategy.

Actuated by the joint rotations of the manipulator, the combined system is driven from three-axis tumbling state to uniaxial rotation about its maximum principal axis. Only unidirectional thrust perpendicular to the axis is needed to slow down the uniaxial rotation, thus saving the thruster fuel. The optimization problem of the collision-free detumbling trajectory of the space robot is described, and it is optimized by the particle swarm optimization algorithm.

The numerical simulation results show that along the trajectory planned by the detumbling strategy, the maneuver of the manipulator can precisely drive the combined system to rotate around its maximum principal axis, and the final kinetic energy of the combined system is smaller than the initial. The unidirectional thrust and the lower kinetic energy can ensure the fuel-saving in the subsequent detumbling stage.

This paper presents a post-capture detumbling strategy to drive the combined system from three-axis tumbling state to uniaxial rotation about its maximum principal axis by redistributing the angular momentum of the parts of the combined system. The strategy reduces the thrust torque for detumbling to effectively save the thruster fuel.

The purpose of this paper is to present an on-orbit frequency identification method for spacecraft directly using attitude maneuver data. Natural frequency of flexible solar arrays plays an important role in attitude control design of spacecraft with solar arrays, and its precision will directly affect the accuracy of attitude maneuver. However, when the flexibility of the solar arrays is large, because of air damping, gravity effect etc., the frequency obtained by ground test shows great error compared with the on-orbit real value. One solution to this problem is to conduct on-orbit identification during which proper identification methods are used to obtain the parameters of interest based on the real on-orbit data of spacecraft.

The observer/Kalman filter identification and eigensystem realization algorithm are used as identification methods, and the attitude maneuver controller is designed using the rigid-body dynamics method.

Two conclusions are drawn in this paper according to results of numerical simulations. The first one is that the attitude controller based on the rigid-body dynamics method is effective in attitude maneuver of the spacecraft. The second one is that the on-orbit parameter identification can be directly achieved by using attitude maneuver data of spacecraft without adding additional missions.

Based on the methods proposed in this paper, it is convenient to obtain the natural frequencies of the spacecraft using the data of the attitude maneuver, which may greatly reduce the cost of on-orbit identification test.

The way of obtaining natural frequencies based on attitude maneuver data of spacecraft provides high originality and value for practical application.

The purpose of this study is to investigate the deployment and control of cable-driven flexible solar arrays.

First, dynamic model of the system is established by using the Jourdain’s velocity variation principle and the single direction recursive construction method, including the dynamic equation of a single flexible body, the kinematical recursive relation of two adjacent flexible bodies and the dynamic equation of the solar array system. Then, the contribution of joint friction to the dynamic equation of the system is derived based on the virtual power principle. A three-dimensional revolute joint model is introduced and discussed in detail. Finally, a proportion-differentiation (PD) controller is designed to control the drift of the system caused by the deployment.

Simulation results show that the proposed model is effective to describe the deployment of flexible solar arrays, joint friction may affect the dynamic behavior of the system and the PD controller can effectively eliminate the spacecraft drift.

This model is useful to indicate the dynamics behavior of the solar array system with friction.

The relationship between ideal constraint force and Lagrange multipliers is derived. The contribution of joint friction to the dynamic equation of the system is derived based on the virtual power principle. A PD controller is designed to control the drift of the system caused by the deployment of solar arrays.

The purpose of this paper is to present a method to obtain the inertia parameter of a captured unknown space target.

An inertia parameter identification method is proposed in the post-capture scenario in this paper. This method is to resolve parameter identification with two steps: coarse estimation and precise estimation. In the coarse estimation step, all the robot arms are fixed and inertia tensor of the combined system is first calculated by the angular momentum conservation equation of the system. Then, inertia parameters of the unknown target are estimated using the least square method. Second, in the precise estimation step, the robot arms are controlled to move and then inertia parameters are once again estimated by optimization method. In the process of optimization, the coarse estimation results are used as an initial value.

Numerical simulation results prove that the method presented in this paper is effective for identifying the inertia parameter of a captured unknown target.

The presented method can also be applied to identify the inertia parameter of space robot.

In the classic momentum-based identification method, the linear momentum and angular momentum of system, both considered to be conserved, are used to identify the parameter of system. If the elliptical orbit in space is considered, the conservation of linear momentum is wrong. In this paper, an identification based on the conservation of angular momentum and dynamics is presented. Compared with the classic momentum-based method, this method can get a more accurate identification result.

This paper aims to present a combination modeling method using multi-source information in the process to improve the accuracy of the dimension propagation relationship for assembly variation reduction.

Based on a variable weight combination prediction method, the combination model that takes the mechanism model and data-driven model based on inspection data into consideration is established. Furthermore, the combination model is applied to qualification rate prediction for process alarming based on the Monte Carlo simulation and also used in engineering tolerance confirmation in mass production stage.

The combination model of variable weights considers both the static theoretical mechanic variation propagation model and the dynamic variation relationships from the regression model based on data collections, and provides more accurate assembly deviation predictions for process alarming.

A combination modeling method could be used to provide more accurate variation predictions and new engineering tolerance design procedures for the assembly process.

The purpose of this paper is to examine whether the type of ultimate controllers (i.e. private vs state) affects corporate disclosure quality and whether the relationship between the type of ultimate controllers and corporate disclosure quality is moderated by the separation of ownership and control.

This study employs the data of 405 Chinese listed firms in 2005. Annual reports were reviewed to collect the data including the type of ultimate owners, cash‐flow rights, and control rights; and the ratings of corporate disclosure quality were obtained from the Shenzhen Stock Exchange website. Ordered logistic regression tested the hypotheses.

It was found that corporate disclosure quality is lower for firms ultimately controlled by individuals than for firms ultimately controlled by the state. Also, the negative effect of private ultimate ownership on corporate disclosure quality is stronger for firms with high deviation of cash‐flow rights and control rights.

These findings suggest that privatizing state‐owned companies may increase the expropriation of minority shareholders by controlling shareholders if the privatization does not reduce the separation of cash‐flow rights from control rights. Thus, it may be necessary to strengthen the governance role of minority shareholders and constrain the divergence between cash‐flow rights and control rights of the ultimate owners when state‐owned companies are privatized.

This study contributes to the literature on the expropriation of minority shareholders by examining the main effect of the type of ultimate controllers and the interactive effect of ultimate ownership type and the divergence of ownership and control on corporate disclosure quality.

The purpose of this paper is to present a visualization platform to control and monitor wireless sensor networks (WSNs) in manufacturing applications.

To make the platform flexible and versatile, a modular framework is adopted in modeling and visualizing WSNs. The Eclipse programming environment is used to maximize the scalability and adaptability of the platform. A set of the core functional modules have been designed and implemented to support the system operation. The platform is validated through a case study simulation.

The platform is capable of accommodating different operating systems such as Windows and Linux. It allows integrating new plug-ins developed in various languages such as Java, C, C++, and Matlab. The Graphic User Interface has been applied to process and visualize the acquired real-time data from a WSN, and the embodied methodologies can be used to predict the behaviors of objects in the network.

The work has shown the feasibility and potential of the proposed platform in improving the real-time performance of WSN. However, the number of the developed functional modules is limited, and additional effort is required to develop sophisticated functional modules or sub-systems for a customized application.

The platform can be applied to monitor and visualize various WSN applications in manufacturing environments such as automated workcells, transportation systems, logistic, and storage systems.

The work is motivated by the scarce research on the development tools for monitoring and visualization of WSNs in manufacturing applications. The proposed platform serves for both of system developers and users. It is modularized with a set of core functional modules; it can be extended to accommodate new functional modules with a minimal effort for a different application.

The purpose of this paper is to develop an information system which is based on the Internet of things (IoT) and used to support the communication and coordination in a cooperative robot team.

The architecture of the IoT applications for decision-making activities in a complex system is elaborated, the focus lies on the effective implementation of system interactions at the device-level. A case study is provided to verify system performances.

The IoT concept has been introduced in an information system of a football robot team to support the coordination among team players. Various sensors are used to collect data from IoT, and data are processed for the controls of robotic players to achieve the better performance at the system level. The field test has shown the feasibility and effectiveness.

To investigate how IoT can be utilized in an information system for making complex decisions effectively, the authors use the decision-support system for a football robot team to illustrate the approaches in developing data acquisition infrastructure, processing and utilizing real-time data for the communication and coordination of robot players in a dynamic competing environment. While the presented work has shown the feasibility of an IoT-based information system, more work are needed to integrate advanced sensors within the IoT and develop more intelligent algorithms to replace manually remote control for the operations of robot players.

The proposed system is specifically for a football robot team; however, the associated approaches are applicable to any decentralized system for developing an information system to support IoT-based communication and coordination within the system in the real-time mode.

The exploration of IoT applications is still at its early stage, existing relevant work is mostly limited to the development of system architecture, sensor networks, and communication protocols. In this paper, the methods on how to use massive real-time data for decision-making of a decentralized team have been investigated, and the proposed system has its theoretical significance to developing other decentralized wireless sensor networks and decision-making systems.

The purpose of this paper is to provide a feasible scheme for local governments to regulate corporate environmental data fraud and to discuss whether the influence of the construction of online information disclosure platform on the environmental behavior of enterprises is better than the offline spot check.

Under the background of changing environmental fees into taxes in China, this paper conducts evolutionary game analysis between local governments and enterprises in view of the existing problem of environmental data fraud. Furthermore, through the introduction of government information disclosure platform, this paper discusses the impact of the integration of direct government regulation and indirect public concern regulation on the evolution of environmental behavior of both sides. Finally, the evolutionary game is simulated by adopting system dynamics to analyses the implementation effect of different cases on the game process and game equilibrium.

The results showed that the introduction of information disclosure platform mechanism can effectively suppress the fluctuations existing in the game play and stabilize the game. Moreover, it is worth noting that the regulatory effect of local governments investing part of the monitoring cost in the construction of online information platform is proved to be better than that of putting all the monitoring cost into offline investigation. While optimizing the monitoring cost allocation, the local government still needs to attach great importance to organically combine the attention of the public and media with the governmental official platform.

The obtained results confirm that the proposed model can assist local government in refining the effects of their environmental regulatory decisions, especially in the case of corporate data fraud under environmental tax enforcement.

Previous literature only suggested that local governments should reduce the cost of supervision to change the corporate behavior to a better direction, but no further in-depth study. Thus, this study fills the gap by discussing the positive transformation effect of local government cost allocation scheme on corporate environmental behavior.