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The cluster spacecraft are instrumented with ion emitters for charge neutralization. The emitters produce indium ions at 6 keV. The ion current is adjusted in a feedback loop with instruments measuring the spacecraft potential. The system is based on the evaporation of indium in the apex field of a needle. The design of the active spacecraft potential control instruments, and the ion emitters is presented.
Active flutter suppression has been demonstrated in simulation by many researchers, generally using methods based on linear aerodynamics and often with simplistic geometries. In this paper, active flutter suppression is demonstrated in a simulation using a Navier-Stokes aerodynamics code, FUN3D (Fully Unstructured Navier-Stokes Three-Dimensional), and a realistic transport aircraft configuration. This is accomplished using simple observer-feedback controllers derived from linear aeroelastic models, including reduced order models built via FUN3D data. The development of these reduced order models is described here. It is shown that controllers derived from reduced order models of the nonlinear aerodynamics outperform controllers based on linear aerodynamics.
NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript "Hydroclimatic Memory and Watershed Template Shape Stream Intermittency: Multi-scale Attribution Using Process-based Simulation and Explainable ML" by Niroula et al. (2026), submitted to Water Resources Research (WRR). The study investigates the dominant controls on stream intermittency across local, reach, and watershed scales using a coupled process-based simulation and explainable machine-learning framework. Long-term daily simulations from the Advanced Terrestrial Simulator (ATS) were used to generate wetness states and ponded-depth responses over river-corridor cells. These ATS outputs were then aggregated across scales and used to train XGBoost (eXtreme Gradient Boosting) models. SHAP (SHapley Additive exPlanations) was applied to quantify the relative importance of hydroclimatic forcings, watershed template attributes, and antecedent-memory effects in shaping intermittency behavior. The analysis is carried out for three contrasting Pacific Northwest watersheds: Oak Creek (OCW), American River Watershed (ARW), and H.J. Andrews (HJA). Across these testbeds, the package contains ATS-ready watershed inputs, ATS run configuration and selected output files, model-evaluation data products, intermittency-analysis datasets, machine-learning target-feature tables, SHAP outputs, and notebooks used to organize, analyze, and visualize results. At a high level, the package documents a workflow in which ATS provides the physically based simulation backbone and explainable machine learning is used as a post-processing attribution tool. The contents are intended to support interpretation of the manuscript figures and results, provide context for how intermittency metrics were generated at multiple scales, and preserve the key artifacts needed to understand and reuse the analysis workflow. The package contains a high-level directory summary file (`summary.txt`) and four main content folders (1) `evaluation_plots` contains evaluation figures and supporting evaluation datasets; (2) `intermittency_plots` contains intermittency-focused analysis notebook and prepared datasets; (3) `ml-training-and-shap_values_plots` contains ML training inputs, SHAP outputs, and figure-generation notebooks; and (4) `watershed_mesh_and_ats_input` contains ATS model setup materials, forcing inputs, geometry, and selected run files. More specifically, the `evaluation_plots` folder contains the notebook used for ATS evaluation plotting and site-specific evaluation datasets. These include evapotranspiration and water-balance products for three watersheds, as well as an Oak Creek field-measurement discharge file. The `intermittency_plots` folder contains the notebook used for intermittency analysis and the prepared datasets used to analyze intermittent and non-intermittent wetness behavior across the study watersheds. The `ml-training-and-shap_values_plots` folder contains notebooks and outputs for the machine-learning and explainability workflow. This includes the main XGBoost and SHAP notebook(s), a beeswarm plotting notebook, target-feature tables for machine-learning training, SHAP summary tables, and per-sample SHAP value archives. The `watershed_mesh_and_ats_input` folder contains ATS-related watershed inputs and supporting materials. This includes mesh and shape products, ATS-readable LAI and meteorological forcing inputs, selected ATS spinup and transient-run files, and a watershed workflow example notebook. Subdirectories are organized by watershed where applicable.All files are .cpg (codepage files), .csv (comma-separated values), .dbf (database files), .exo (Exodus mesh format), .h5 (HDF5 format), .ipynb (Jupyter notebooks), .pkl (Python pickle), .prj (projection files), .sh (shell scripts), .shp (shapefile geometry), .shx (shapefile index), .txt (text files), or .xml (markup data).
ABSTRACT Many bacteria utilize the type 9 secretion system (T9SS) for gliding motility, surface colonization, and pathogenesis. This dual-function motor supports both gliding motility and protein secretion, where rotation of the T9SS plays a central role. Fueled by the energy of the stored proton motive force and transmitted through the torque of membrane-anchored stator units, the rotary T9SS propels an adhesin-coated conveyor belt along the bacterial outer membrane like a molecular snowmobile, thereby enabling gliding motion. However, the mechanisms controlling the rotational direction and gliding motility of T9SS remain elusive. Shedding light on this mechanism, we find that in the gliding bacteriumFlavobacterium johnsoniae, deletion of the C-terminus of the conveyor belt-associated protein GldJ controls and, in fact, reverses the rotational direction of T9SS from counterclockwise (CCW) to clockwise (CW). This suggests that the interface between the conveyor belt-associated protein GldJ and the T9SS ring protein GldK plays an important role in controlling the directionality of T9SS, potentially by modulating its interaction with the stator complex GldLM, which drives motor rotation. Combined with MD simulation of the T9SS stator units GldLM, we suggest a “tri-component gearset” model where GldJ controls the rotational direction of its driver, the T9SS, thus providing adaptive sensory feedback to influence the motility of the gliding bacterium. IMPORTANCE The type 9 secretion system (T9SS) is fundamental to bacterial gliding motility, pathogenesis, and surface colonization. Our findings reveal that the C-terminal region of the conveyor belt-associated protein GldJ functions as a molecular switch which is capable of reversing the rotational direction of T9SS. Through the coordinated actions of the T9SS stator units (akin to a driving motor), the GldK ring (the gear that converts rotational energy into linear movement), and GldJ, this machinery forms a smart conveyor belt system reminiscent of flexible or cognitive mechanical conveyors. Such advanced conveyors can alter their direction to adapt to shifting demands. Here, we show that the bacterial T9SS similarly adjusts its rotational bias based on feedback from the conveyor belt-associated protein GldJ. This dual-role feedback mechanism underscores an evolved, controllable biological snowmobile, offering new avenues for studying how bacteria fine-tune motility in dynamic environments.
Nanometer-scale shape control of x-ray mirrors is crucial for coherent x-ray beam experiments at low-emittance synchrotron beamline instruments. Piezoelectric bimorph mirrors offer adaptive control but are hindered by nonlinearities such as cross talk, creep, and hysteresis. To overcome these limitations, we present a novel feedback-free control solution, inspired by the proportional–integral–derivative (PID) scheme, driven by tandem neural networks (TNNs). Using task-specific datasets, the TNN-based system predicts actuator voltages with greater speed, accuracy, and stability than a single NN-based model. This approach is ideal for real-time applications, such as adapting beam focus to dynamic sample sizes while maintaining precise wavefront quality. Our findings highlight the potential of artificial intelligence in rapidly optimizing adaptive optics and managing nonlinear control systems.
A stability and control augmentation system (SCAS) was designed based on a set of comprehensive performance criteria. Linear optimal control theory was applied to determine appropriate feedback gains for the stability augmentation system (SAS). The helicopter was represented by six-degree-of-freedom rigid body equations of motion and constant factors were used as weightings for state and control variables. The ratio of these factors was employed as a parameter for SAS analysis and values of the feedback gains were selected on this basis to satisfy three of the performance criteria for full and partial state feedback systems. A least squares design method was then applied to determine control augmentation system (CAS) cross feed gains to satisfy the remaining seven performance criteria. The SCAS gains were then evaluated by nine degree-of-freedom equations which include flapping motion and conclusions drawn concerning the necessity of including the pitch/regressing and roll/regressing modes in SCAS analyses.
Recently Zames (1981) has introduced the so-called model reference transformation which can be used to conveniently parameterize the class of linear time-invariant multivariable compensators that lead to stable feedback control systems. A very popular design methodology for designing stable and robust multivariable control systems is that based on the Linear-Quadratic-Gaussian (LQG) methodology with Loop Transfer Recovery (LTR). Thus, it is natural to inquire upon the relationship between the Zames representation and the LQG/LTR compensators. This paper summarizes this relationship.
A new method has been developed for the growth of graded band-gap Al(x)Ga(1-x)As alloys by molecular beam epitaxy which is based upon electron beam evaporation of the group III elements. The metal fluxes are measured and feedback controlled using a modulated ion gauge sensor. The system is computer controlled which allows precise programming of the Ga and Al evaporation rates. The large dynamic response of the metal sources enables growth of variable band-gap III-V alloys with arbitrary composition profiles. This new technique is demonstrated by synthesis of analog graded Al(x)Ga(1-x)As unipolar ballistic electron transistors.
The sensitivity of actively damped response of structures with respect to errors in the structural modeling is studied. Two ways of representing errors are considered. The first approach assumes errors in the form of spatial variations (or imperfections) in the assumed mass and stiffness properties of the structures. The second approach assumes errors due to such factors as unknown joint stiffnesses, discretization errors, and nonlinearities. These errors are represented here as discrepancies between experimental and analytical mode shapes and frequencies. The actively damped system considered here is a direct-rate feedback regulator based on a number of colocated velocity sensors and force actuators. The response of the controlled structure is characterized by the eigenvalues of the closed-loop system. The effects of the modeling errors are thus presented as the sensitivity of the eigenvalues of the closed-loop system. Results are presented for two examples: (1) a three-span simply supported beam controlled by three sensors and actuators, and (2) a laboratory structure consisting of a cruciform beam supported by cables.
Efficient compression of image data requires the understanding of the noise characteristics of sensors as well as the redundancy expected in imagery. Herein, the techniques of Differential Pulse Code Modulation (DPCM) are reviewed and modified for information-preserving data compression. The modifications include: mapping from intensity to an equal variance space; context dependent one and two dimensional predictors; rationale for nonlinear DPCM encoding based upon an image quality model; context dependent variable length encoding of 2x2 data blocks; and feedback control for constant output rate systems. Examples are presented at compression rates between 1.3 and 2.8 bits per pixel. The need for larger block sizes, 2D context dependent predictors, and the hope for sub-bits-per-pixel compression which maintains spacial resolution (information preserving) are discussed.
The automated alignment system, described herein, employs a reflective, passive (requiring no power) target and includes a PC-based imaging system and one camera mounted on a six degree of freedom robot manipulator. The system detects and corrects for manipulator misalignment in three translational and three rotational directions by employing the Targeting and Reflective Alignment Concept (TRAC), which simplifies alignment by decoupling translational and rotational alignment control. The concept uses information on the camera and the target's relative position based on video feedback from the camera. These relative positions are converted into alignment errors and minimized by motions of the robot. The system is robust to exogenous lighting by virtue of a subtraction algorithm which enables the camera to only see the target. These capabilities are realized with relatively minimal complexity and expense.
The paper presents the synthesis of neural network based feedback laws for dynamic systems using the computed optimal and time histories of the state and control variables. The efficacy of the proposed approach has been successfully demonstrated on a minimum time orbit injection problem. If the method is found to be effective to real life problems with many state and control variables, it can used for a variety of guidance and control problems.
This paper presents an overview of the fifth revision to an algorithm specifically designed to support NASA's Airborne Precision Spacing concept. This algorithm is referred to as the Airborne Spacing for Terminal Arrival Routes version 12 (ASTAR12). This airborne self-spacing concept is trajectory-based, allowing for spacing operations prior to the aircraft being on a common path. Because this algorithm is trajectory-based, it also has the inherent ability to support required-time-of- arrival (RTA) operations. This algorithm was also designed specifically to support a standalone, non-integrated implementation in the spacing aircraft. This current revision to the algorithm includes a ground speed feedback term to compensate for slower than expected traffic aircraft speeds based on the accepted air traffic control tendency to slow aircraft below the nominal arrival speeds when they are farther from the airport.
The crew on-board the International Space Station (ISS) have to be prepared for any possible emergency. The emergencies of most concern are a fire, depressurization or a toxic atmosphere. The crew members train on the ground before launch but also need to practice their emergency response skills while they are on orbit for 6 months. On-Board Training (OBT) events for emergency response proficiency used to require the crew and ground teams to use paper "scripts" that showed the path through the emergency procedures. This was not very realistic since the participants could read ahead and never deviate from this scripted path. The new OBT emergency simulator allows the crew to view dynamic information on an iPad only when it would become available during an event. The simulator interface allows the crew member to indicate hatch closures, don and doff masks, read pressures, and sample smoke or atmosphere levels. As the crew executes their actions using the on-board simulator, the ground teams are able to monitor those actions via ground display data flowing through the ISS Ku Band communication system which syncs the on-board simulator software with a ground simulator which is accessible in all the control centers. The OBT Working Group (OBT WG), led by the Chief Training Office (CTO) at Johnson Space center is a Multilateral working group with partners in Russia, Japan, Germany and U.S.A. The OBTWG worked together to create a simulator based on these principles: (a) Create a dynamic simulation that gives real-time data feedback; (b) Maintain real-time interface between Mission Control Centers and crew during OBTs; (c) Provide flexibility for decision making during drill execution; (d) Materially reduce Instructor and Flight Control Team man-hour costs involved with developing, updating, and maintaining emergency OBT cases/scenarios; and (e) Introduce an element of surprise to emergency scenarios so the team can't tell the outcome of the case by reading ahead in a paper script. This paper details some of the background as the project evolved with the International Partners. It also provides more details on how the simulator information for the crew is also shared with the ground teams. Finally, the paper will discuss how this remote simulator concept can be useful for future, longer term space missions.
We present a model of cerebellar cortex that combines two types of learning: feedforward predicitve association based on local Hebbian-type learning between granule cell ascending branch and parallel fiber inputs, and reinforcement learning with feedback error correction based on climbing fiber activity.
A schematic description of the steering control process is presented. It is shown that this process can be described in terms of levels of control. Level of control will depend on driver's skill in making use of 'clever' strategies which may be related to knowledge about the path to follow (input) and/or the vehicle under control. This knowledge may be referred to as an internal model of a particular task element. Internal information, as derived from these internal models will probably be used together with proprioceptive feedback. It is hypothesized that the efficiency of the higher levels of control will be dependent on the accuracy of both the internal and proprioceptive information. Based on this research philosophy a series of experiments is carried out. Two primary experiments were done in order to analyse subjects' ability to reproduce steering-wheel positions and movements without visual feedback. Steering-wheel angle amplitude, steering force and movement frequency were involved as independent variables.
The feasibility of off the shelf eight bit and 16 bit microprocessors to implement linear state variable feedback control laws and assessing the real time response to spacecraft dynamics is studied. The complexity of the dynamic model is described along with the appropriate software. An experimental setup of a beam, microprocessor system for implementing the control laws and the needed generalized software to implement any state variable feedback control system is included.
The concept of a generic module for management of onboard systems grew out of the structured analysis effort for the Space Station software. Hierarchical specification of subsystems software revealed that nontrivial supervisory elements are required at all levels. The number of supervisors (and subsequent software) required to implement the hierarchical control over onboard functions comprise a large portion of the Space Station software. Thus, a generic knowledge based supervisory module significantly reduces the amount of software developed. This module, the Generic Supervisor, depends on its knowledge of control to provide direction for subordinates and feedback to superiors within a specific subsystem area. The Generic Supervisor provides an adaptable and maintainable control system. A portion of the Space Station Environmental Control and Life Support System (ECLSS) was implemented as a hierarchy of supervisors. This prototype implementation demonstrates the feasibility of a generic knowledge based supervisor, and its facility to meet complex mission requirements.