A spacecraft attitude control system provides mechanical and electrical control to achieve the required functions under various mission scenarios. Although generally designed to be highly reliable, ...mission failure can occur if anomalies occur and the attitude control system fails to properly orient and stabilize the spacecraft. Because accessing spacecraft to directly repair such problems is usually infeasible, developing a continuous condition monitoring model is necessary to detect anomalies and respond accordingly. In this study, a method for detecting anomalies and characterizing failures for spacecraft attitude control systems is proposed. Herein, features are extracted from multidimensional time-series data of a simulation of the attitude control system. Then, the artificial neural network learning algorithms based on two types of generation models are applied. A Bayesian optimization algorithm with a Gaussian process is used to optimize the hyperparameters for the neural network to improve the performance. The performance is evaluated based on the reconstruction error through the algorithm using the newly generated data not used for learning as input data. Results show that the detection performance depends on the operating characteristics of each submode in the operation scenarios and type of generation model. The diagnostic results are monitored to detect anomalies in operation modes and scenarios.
This paper addresses task allocation to coordinate a fleet of autonomous vehicles by presenting two decentralized algorithms: the consensus-based auction algorithm (CBAA) and its generalization to ...the multi-assignment problem, i.e., the consensus-based bundle algorithm (CBBA). These algorithms utilize a market-based decision strategy as the mechanism for decentralized task selection and use a consensus routine based on local communication as the conflict resolution mechanism to achieve agreement on the winning bid values. Under reasonable assumptions on the scoring scheme, both of the proposed algorithms are proven to guarantee convergence to a conflict-free assignment, and it is shown that the converged solutions exhibit provable worst-case performance. It is also demonstrated that CBAA and CBBA produce conflict-free feasible solutions that are robust to both inconsistencies in the situational awareness across the fleet and variations in the communication network topology. Numerical experiments confirm superior convergence properties and performance when compared with existing auction-based task-allocation algorithms.
Sutton, Szepesvári and Maei introduced the first gradient temporal-difference (GTD) learning algorithms compatible with both linear function approximation and off-policy training. The goal of this ...paper is (a) to propose some variants of GTDs with extensive comparative analysis and (b) to establish new theoretical analysis frameworks for the GTDs. These variants are based on convex-concave saddle-point interpretations of GTDs, which effectively unify all the GTDs into a single framework, and provide simple stability analysis based on recent results on primal-dual gradient dynamics. Finally, numerical comparative analysis is given to evaluate the new approaches.
This paper presents closed-form optimal cooperative guidance laws for two UAVs under information constraints that achieve the required relative approach angle. Two UAVs cooperate to optimize a common ...cost function under a coupled constraint on terminal velocity vectors and the information constraint which defines the sensor information availability. To handle the information constraint, a general two-player partially nested decentralized optimal control problem is considered in the continuous finite-horizon time domain. It is shown that under the state-separation principle the optimal solution of the decentralized control problem can be obtained by solving two centralized subproblems which cover the prediction problem for the information-deficient player and the prediction error minimization problem for the player with full information. Based on the solution of the decentralized optimal control problem, the explicit closed-form cooperative guidance laws that can be efficiently implemented on conventional guidance computers are derived. The performance of the proposed guidance laws is investigated on both centralized and decentralized cooperative scenarios with nonlinear engagement kinematics of networked two-UAV systems.
Background The purpose of this study was to investigate clinical and radiologic outcomes of clavicle hook plate fixation for distal-third clavicle fracture (Neer type II) and to compare the clinical ...and radiologic outcomes and complications between Neer type IIA and type IIB. Methods We retrospectively reviewed 35 patients who underwent open reduction and internal fixation with AO hook locking compression plate (LCP) for distal clavicle fracture, including 13 patients with Neer type IIA and 22 patients with type IIB. Visual analog scale pain score, shoulder scores (subjective shoulder value, University of California–Los Angeles shoulder score, American Shoulder and Elbow Surgeons score), and active range of motion were evaluated to determine clinical outcome. Coracoclavicular distance was measured, and that of the injured side at last follow-up was compared with that of the uninjured side to evaluate radiologic outcomes. Results AO hook LCP fixation for distal-third clavicle fracture (Neer type II) produced satisfactory radiologic outcomes, including high union rates (100%) and coracoclavicular distance maintenance, as well as satisfactory clinical outcomes, including visual analog scale score for pain, shoulder scores (subjective shoulder value, University of California–Los Angeles shoulder score, American Shoulder and Elbow Surgeons score), and active range of motion. There were no significant differences between Neer type IIA and type IIB. With regard to complications, 22.9% of patients experienced shoulder stiffness and 17.1% had subacromial erosion; however, there were no significant differences between the 2 groups. Conclusion The AO hook LCP is a suitable choice for Neer type IIA and type IIB distal-third clavicle fracture fixation.
This paper proposes a novel approach for guidance law design to satisfy the impact-time constraints for a certain class of homing missiles. The proposed guidance law provides proper lateral ...acceleration commands that make the impact time error converge to zero by the time of impact. This scheme can be applied to any existing guidance law for which a formula of predicted time to go is available. Convergence of time-to-go errors is supported by Lyapunov stability. The optimal guidance law and the impact angle control guidance law are extended by the proposed method for impact-time-control guidance and impact-time-and-angle-control guidance, respectively. The performance of the extended guidance laws is demonstrated by numerical simulation.
Spacecraft that rely on self-localization based on optical terrain images require suitable landmark information along their flight paths. When navigating within the vicinity of the moon, a lunar ...crater is an intuitive choice. However, in highland areas or regions having low solar altitudes, craters are less reliable because of heavy shadowing, which results in infrequent and unpredictable crater detections. This paper, therefore, presents a method for suggesting navigation landmarks that are usable, even with unfavorable illumination and rough terrain, and it provides a procedure for applying this method to a lunar flight plan. To determine a good landmark, a convolutional neural network (CNN)-based object detector is trained to distinguish likely landmark candidates under varying lighting geometries and to predict landmark detection probabilities along flight paths attributable to various dates. Dates having more favorable detection probabilities can be determined in advance, providing a useful tool for mission planning. Numerical experiments show that the proposed landmark detector generates usable navigation information at sun elevations of less than 1.8° in highland areas.
This paper addresses multi-target tracking using a monocular vision sensor. To overcome the fundamental observability issue of the monocular vision, a convolutional neural network (CNN)-based method ...is proposed. The method combines a CNN-based multi-target detection into a model-based multi-target tracking framework. While previous CNN applications to image-based object recognition and tracking focused on prediction of region of interest (RoI), the proposed method allows for prediction of the three-dimensional position information of the moving objects of interest. This is achieved by appropriately construct a network tailored to the moving object tracking problems with potentially occluded objects. In addition, the cubature Kalman filter integrated with a data association scheme is adopted for effective tracking of nonlinear motion of the objects with the measurements information from the learned network. A virtual simulator that generates the trajectories of the target motions and a sequence of images of the scene has been developed and used to test and verify the proposed CNN scheme. Simulation case studies demonstrate that the proposed CNN improves the position accuracy in the depth direction substantially.
Chronic stress causes maladaptive changes in the brain that lead to depressive behavior. In the present study, we investigate whether chronic stress alters gut microbiota compositions that are ...related to stress-induced maladaptive changes in the brain. Mice treated with daily 2-h restraint for 14 days (CRST) exhibit depressive-like behavior. Sequence readings of 16S rRNA genes prepared from fecal samples taken from CRST-treated mice suggest that chronic stress induces gut microbiota changes that are pronounced in the post-stress period, relative to those that occur in the 14-day stress phase. The genus
Lactobacillus
is one such microbiota substantially changed following chronic stress. In contrast, intraperitoneal injection of extracellular vesicles (EVs) isolated from culture media of the Gram-positive probiotic
Lactobacillus plantarum
is sufficient to ameliorate stress-induced depressive-like behavior. Interestingly, EVs from the Gram-positive probiotic
Bacillus subtilis
and EVs from the Gram-negative probiotic
Akkermansia muciniphila
also produce anti-depressive-like effects. While chronic stress decreases the expression of MeCP2, Sirt1, and/or neurotrophic factors in the hippocampus, EVs from the three selected probiotics differentially restore stress-induced changes of these factors. These results suggest that chronic stress produces persistent changes in gut microbiota composition, whereas purified EVs of certain probiotics can be used for treatment of stress-induced depressive-like behavior.
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