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At least 1,801 records · Page 100

Immobile Robots: AI in the New Millennium

A new generation of sensor rich, massively distributed, autonomous systems are being developed that have the potential for profound social, environmental, and economic change. These include networked building energy systems, autonomous space probes, chemical plant control systems, satellite constellations for remote ecosystem monitoring, power grids, biosphere-like life support systems, and reconfigurable traffic systems, to highlight but a few. To achieve high performance, these immobile robots (or immobots) will need to develop sophisticated regulatory and immune systems that accurately and robustly control their complex internal functions. To accomplish this, immobots will exploit a vast nervous system of sensors to model themselves and their environment on a grand scale. They will use these models to dramatically reconfigure themselves in order to survive decades of autonomous operations. Achieving these large scale modeling and configuration tasks will require a tight coupling between the higher level coordination function provided by symbolic reasoning, and the lower level autonomic processes of adaptive estimation and control. To be economically viable they will need to be programmable purely through high level compositional models. Self modeling and self configuration, coordinating autonomic functions through symbolic reasoning, and compositional, model-based programming are the three key elements of a model-based autonomous systems architecture that is taking us into the New Millennium.

Williams, Brian C.↗

Simulation of an Electromechanical Spin Motor System of a Control Moment Gyroscope

A two-phase brushless DC motor (BDCM) with pulse-width modulated (PWM) voltage drive is simulated to control the flywheel speed of a control moment gyroscope (CMG). An overview of a double-gimballed control moment gyroscope (DGCMG) assembly is presented along with the CMG torque effects on the spacecraft. The operating principles of a two-phase brushless DC motor are presented and the system's electro-mechanical equations of motion are developed for the root-mean-square (RMS) currents and wheel speed. It is shown that the system is an extremely "stiff" set of first-order equations for which an implicit Euler integrator is required for a stable solution. An adaptive proportional voltage controller is presented which adjusts the PWM voltages depending on several control modes for speed, current, and torque. The simulation results illustrate the interaction between the electrical system and the load dynamics and how these influence the overall performance of the system. As will be shown, the CMG spin motor model can directly provide electrical power use and thermal power output to spacecraft subsystems for effective (average) calculations of CMG power consumption.

Inampudi, Ravi↗

Nonlinear filtering and limiting in high order methods for ideal and non-ideal MHD

The various filtering mechanisms and base scheme options of the newly developed adaptive numerical dissipation control in spatially high order filter schemes for the ideal and non-ideal magnetohydrodynamics (MHD) equations are investigated. These filter schemes are applicable to complex unsteady MHD high-speed shock/shear/turbulence problems. They also provide a natural and efficient way for the minimization of Div(B) numerical error. The type of spatial base scheme to be used in conjunction with our filter idea is very general. For example, spectral, compact and non-compact spatially central finite difference schemes are possible candidates. The adaptive numerical dissipation mechanism consists of automatic detection of different flow features as distinct sensors to signal the appropriate type and amount of numerical dissipation/filter where needed and to leave the rest of the region free from numerical dissipation contamination. The numerical dissipation considered consists of high order linear dissipation for the suppression of high frequency oscillation and the nonlinear dissipative portion of high-resolution shock-capturing methods for discontinuity capturing. The applicable nonlinear dissipative portion of high-resolution shock-capturing methods is also very general. The objective of this paper is to investigate the performance of using compact and non-compact central base schemes in conjunction with three commonly used types of nonlinear numerical dissipation for both the ideal and non-ideal MHD. This extended abstract shows the performance of three nonlinear filters in conjunction with a sixth-order non-compact spatial central base scheme. In the final paper, the high order compact spatial central base scheme will be illustrated and compared with the non-compact base scheme. The reason for the investigation of the high order compact spatial central base scheme over the non-compact base scheme is to evaluate if additional accuracy can be gained in regions of fine scale turbulence that are away from shocks/shears.

Yee,H. C.↗

Towards Resilient Autonomous Navigation of Drones

Robots and particularly drones are especially useful in exploring extreme environments that pose hazards to humans. To ensure safe operations in these situations, usually perceptually degraded and without good GNSS, it is critical to have a reliable and robust state estimation solution. The main body of literature in robot state estimation focuses on developing complex algorithms favoring accuracy. Typically, these approaches rely on a strong underlying assumption: the main estimation engine will not fail during operation. In contrast, we propose an architecture that pursues robustness in state estimation by considering redundancy and heterogeneity in both sensing and estimation algorithms. The architecture is designed to expect and detect failures and adapt the behavior of the system to ensure safety. To this end, we present HeRO (Heterogeneous Redundant Odometry): a stack of estimation algorithms running in parallel supervised by a resiliency logic. This logic carries out three main functions: a) perform confidence tests both in data quality and algorithm health; b) re-initialize those algorithms that might be malfunctioning; c) generate a smooth state estimate by multiplexing the inputs based on their quality. The state and quality estimates are used by the guidance and control modules to adapt the mobility behaviors of the system. The validation and utility of the approach are shown with real experiments on a ying robot for the use case of autonomous exploration of subterranean environments, with particular results from the STIX event of the DARPA Subterranean Challenge.

Agha-mohammadi, Ali-akbar↗

Managing the techno-economic impacts of partial string failure in multistring energy storage systems

The role of energy storage systems (ESSs) is becoming increasingly important for today’s electric power systems. Unavailability of an ESS assigned to critical grid services may cause unwanted disruption of those services and hence, may have a significant techno-economic impact. Like any physical equipment, an ESS is vulnerable to various types of faults. Failure of one or more strings in a multistring ESS does not have to be the cause of shutting down the entire ESS. It can still operate with a partial number of strings and continue providing critical services to the grid, if there are no reliability or safety issues and is acceptable under applicable standards. However, it is important to make sure that the control strategies are adaptable to the changes in ESS capacity caused by failed strings. Also, depending on the previous operation and type of failure, the reallocation of duty cycle burden among available strings could be non-uniform. These complexities suggest that mitigation of the impact of partial failure in multistring ESSs is not trivial and needs careful consideration. This is the topic of this paper. The proposed work investigates the impact of partial failure of a large multistring ESS on the assigned service and develops strategies to adjust the ESS control duty cycles for reducing such impacts. In doing so, the paper proposes a novel two-stage framework that plans for the multistring failure using robust optimization theory and then adjusts in real-time using a rule-based algorithm, based on the real-time information on the power availability of the string. Illustrations provided in this work are based on frequency regulation use-case, which is a common application for many utility-scale ESSs. A 750 kilowatt (kW)/1500 kilowatt-hour (kWh) 3-string ESS is used for the demonstration in this work and the efficacy of the proposed method is demonstrated and compared against methods that do not incorporate string failure in their strategy. In particular, here we show that revenue loss of 93% can be incurred when partial string failure is not included in operation and planning. These losses in revenue are reduced by 60% with the proposed method.

25 ENERGY STORAGE↗

DACS II - A distributed thermal/mechanical loads data acquisition and control system

A distributed data acquisition and control system has been developed for the NASA Flight Loads Research Facility. The DACS II system is composed of seven computer systems and four array processors configured as a main computer system, three satellite computer systems, and 13 analog input/output systems interconnected through three independent data networks. Up to three independent heating and loading tests can be run concurrently on different test articles or the entire system can be used on a single large test such as a full scale hypersonic aircraft. Thermal tests can include up to 512 independent adaptive closed loop control channels. The control system can apply up to 20 MW of heating to a test specimen while simultaneously applying independent mechanical loads. Each thermal control loop is capable of heating a structure at rates of up to 150 F per second over a temperature range of -300 to +2500 F. Up to 64 independent mechanical load profiles can be commanded along with thermal control. Up to 1280 analog inputs monitor temperature, load, displacement and strain on the test specimens with real time data displayed on up to 15 terminals as color plots and tabular data displays. System setup and operation is accomplished with interactive menu-driver displays with extensive facilities to assist the users in all phases of system operation.

Zamanzadeh, Behzad↗

Signal Whisperers: Enhancing Wireless Reception Using DRL-Guided Reflector Arrays

This paper presents a multi-agent reinforcement learning (MARL) approach for controlling adjustable metallic reflector arrays to enhance wireless signal reception in non-line-of-sight (NLOS) scenarios. Unlike conventional reconfigurable intelligent surfaces (RIS) that require complex channel estimation, our system employs a centralized training with decentralized execution (CTDE) paradigm where individual agents corresponding to reflector segments autonomously optimize reflector element orientation in three-dimensional space using spatial intelligence based on user location information. Through extensive ray-tracing simulations with dynamic user mobility, the proposed multi-agent beam-focusing framework demonstrates substantial performance improvements over single-agent reinforcement learning baselines, while maintaining rapid adaptation to user movement within one simulation step. Comprehensive evaluation across varying user densities and reflector configurations validates system scalability and robustness. The results demonstrate the potential of learning-based approaches for adaptive wireless propagation control.

deep reinforcement learning↗

Optimizing Sensor and Actuator Arrays for ASAC Noise Control

This paper summarizes the development of an approach to optimizing the locations for arrays of sensors and actuators in active noise control systems. A type of directed combinatorial search, called Tabu Search, is used to select an optimal configuration from a much larger set of candidate locations. The benefit of using an optimized set is demonstrated. The importance of limiting actuator forces to realistic levels when evaluating the cost function is discussed. Results of flight testing an optimized system are presented. Although the technique has been applied primarily to Active Structural Acoustic Control systems, it can be adapted for use in other active noise control implementations.

Palumbo, Dan↗

Control in Unmanned NASA Missions

This viewgraph presentation reviews several general aspects of control for NASA space missions. Included in the review are the Entry, Descent and Landing (EDL) for both Mars Exploration Rover (MER), and Mars Science Laboratory (MSL); and the control of the MER Rover. Also included is discussion about control issues in relation to formation flying, adaptive optics and precision wavefront control, sensors for environmental control- ENose. Essential developments in the areas of control are important for increase in Autonomy/Automation is essential for deep space manned missions. Other areas of concern are robustness and the need to address life support system control issues.

wavefront control↗

Effects of Selected Task Performance Criteria at Initiating Adaptive Task Real locations

In the current report various performance assessment methods used to initiate mode transfers between manual control and automation for adaptive task reallocation were tested. Participants monitored two secondary tasks for critical events while actively controlling a process in a fictional system. One of the secondary monitoring tasks could be automated whenever operators' performance was below acceptable levels. Automation of the secondary task and transfer of the secondary task back to manual control were either human- or machine-initiated. Human-initiated transfers were based on the operator's assessment of the current task demands while machine-initiated transfers were based on the operators' performance. Different performance assessment methods were tested in two separate experiments.

Montgomery, Demaris A.↗

The Role of Adaptation in Body Load-Regulating Mechanisms During Locomotion

Body loading is a fundamental parameter that modulates motor output during locomotion, and is especially important for controlling the generation of stepping patterns, dynamic balance, and termination of locomotion. Load receptors that regulate and control posture and stance in locomotion include the Golgi tendon organs and muscle spindles at the hip, knee, and ankle joints, and the Ruffini endings and the Pacinian corpuscles in the soles of the feet. Increased body weight support (BWS) during locomotion results in an immediate reorganization of locomotor control, such as a reduction in stance and double support duration and decreased hip, ankle, and knee angles during the gait cycle. Previous studies on the effect during exposure to increased BWS while walking showed a reduction in lower limb joint angles and gait cycle timing that represents a reorganization of locomotor control. Until now, no studies have investigated how locomotor control responds after a period of exposure to adaptive modification in the body load sensing system. The goal of this research was to determine the adaptive properties of body load-regulating mechanisms in locomotor control during locomotion. We hypothesized that body load-regulating mechanisms contribute to locomotor control, and adaptive changes in these load-regulating mechanisms require reorganization to maintain forward locomotion. Head-torso coordination, lower limb movement patterns, and gait cycle timing were evaluated before and after a 30-minute adaptation session during which subjects walked on a treadmill at 5.4 km/hr with 40% body weight support (BWS). Before and after the adaptation period, head-torso and lower limb 3D kinematic data were obtained while performing a goal directed task during locomotion with 0% BWS using a video-based motion analysis system, and gait cycle timing parameters were collected by foot switches positioned under the heel and toe of the subjects shoes. Subjects showed adaptive modification in the body load-regulating mechanisms that included increased head movement amplitude, increased knee and ankle flexion, and increased stance, stride, and double support time, with no change in the performance of the task with respect to that measured before exposure to BWS. These changes in locomotor control are opposite to that reported during 40% BWS exposure and indicative of an after-effect after removal of the adaptive stimulus. Therefore, it is evident that just 30 minutes of 40% BWS during locomotion was sufficient to induce adaptive modifications in the body load sensing systems that contribute to reorganization of sensory contributions to stable locomotor control.

Ruttley, Tara↗

A control-theory model for human decision-making

A model for human decision making is an adaptation of an optimal control model for pilot/vehicle systems. The models for decision and control both contain concepts of time delay, observation noise, optimal prediction, and optimal estimation. The decision making model was intended for situations in which the human bases his decision on his estimate of the state of a linear plant. Experiments are described for the following task situations: (a) single decision tasks, (b) two-decision tasks, and (c) simultaneous manual control and decision making. Using fixed values for model parameters, single-task and two-task decision performance can be predicted to within an accuracy of 10 percent. Agreement is less good for the simultaneous decision and control situation.

Levison, W. H.↗

An Adaptive Critic Approach to Reference Model Adaptation

Neural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.

Krishnakumar, K.↗

Cellulose-MOFs hybrid materials: Chemistry and mechanism of applications in biomedical - A review

Rising costs and performance limits of modern biomedical materials motivate the search for advanced, biocompatible alternatives. Cellulose-based metal-organic frameworks (cellulose-MOFs) emerge as distinctive hybrids combining renewable polymer chemistry with tunable porous architectures, enabling uncommon structure–function relationships. Their large surface area, controllable pore size, adaptable functional groups, and efficient host–guest interactions underpin diverse biomedical functions. Till now, no comprehensive, application-focused review has systematically summarized cellulose-MOFs synthesis for biomedical applications. This review critically analyzes cellulose-MOFs, emphasizing mechanistic links between chemistry, synthesis routes, interfacial interactions, and biomedical performance, rather than cataloging applications alone. Antibacterial action, targeted drug delivery, and sensing/biosensing are discussed through comparative insights. The article identifies unresolved challenges and proposes future research pathways to rationally design next-generation cellulose-MOFs systems, guiding researchers and clinicians alike.

Biomedical↗

Intra-catalyst CH 4 oxidation pathways on a Pd/Al 2 O 3 /CeZrO x -based commercial catalyst and implications on NO x conversion profiles for a natural gas vehicle exhaust under lambda modulation

The performance of a three-way catalyst (TWC) in natural gas-powered vehicles is enhanced by periodic changes in air-to-fuel ratio (λ-modulation). The reaction networks and sequences inside the catalyst that facilitate such enhanced performance have not been extensively investigated. Here, this work applied intra-catalyst measurements (SpaciMS) to analyze the transient spatiotemporal gas concentrations inside a Pd-based TWC to establish relationships between CH 4 , NO x , CO and H 2 conversion pathways. Steam reforming and partial oxidation were revealed to be the main CH 4 conversion routes. The cyclic rich-lean conditions combined with the oxygen storage capacity (OSC) of the TWC generate reduced and oxidized zones that are constantly moving within the catalyst, changing the dominant chemical reactions occurring on the surface. In the reduced zones, OSC is depleted while CH 4 is converted through steam reforming and NO x is converted through reactions with H 2 , CO, and other surface-bound reducing fragments formed by CH 4 conversion. In the oxidized zones, OSC is replenished, CH 4 is converted by partial oxidation, and H 2 , CO, and NH 3 are oxidized. The length of lean-rich phases impacts the catalyst performance significantly; too short or too long of a rich or lean phase can lower the overall conversion of reactive species. An inhibition of CH 4 conversion was observed during the rich phase possibly due to CO-poisoning of active sites. The intra-catalyst measurements revealed that the catalyst consists of three distinct reaction zones and their lengths vary with modulation conditions. Various modulation frequencies, amplitudes, λ-centers, and temperatures were investigated which allowed an understanding of how these parameters affect the reaction zones and catalyst utilization. Understandings from this work can enable adaptive λ-control strategies to optimize the overall TWC performance over a range of vehicle operating conditions.

Lean-Rich cycling↗

Magnus method for electronic structure calculations at extreme conditions

We present the application of Magnus based methods to the solution of first order coupled ordinary differential equations in High Energy Density (HED) physics applications. Our focus is on the application to quantum mechanical methods, specifically on the solution of the radial Dirac equation for real and complex energies. HED applications require accurate solutions across a wide range of spatial and energy domains, including regimes where the solutions exhibit pronounced oscillatory behavior. Such cases pose significant computational challenges. We demonstrate that Magnus-based integrators can efficiently and accurately address these challenges. We discuss the implementation of the Magnus method for the solution of the radial Dirac equation, including practical considerations such as the evaluation of matrix exponentials, numerical integration, error estimation, and adaptive step size control. We also discuss the application of these methods to complex energy Green’s function techniques and the efficient approximation of integrals of the solutions relevant to HED electronic structure calculations. Here, we demonstrate the accuracy and robustness of the resulting method in applications to the free-particle case, for which analytic solutions are available for comparison, as well as the challenging case of gold at HED conditions.

general physics↗

Compressed Sensing of Scanning Transmission Electron Microscopy (STEM) With Nonrectangular Scans

Scanning transmission electron microscopy (STEM) has become the main stay for materials characterization on atomic level, with applications ranging from visualization of localized and extended defects to mapping order parameter fields. In recent years, attention has focused on the potential of STEM to explore beam induced chemical processes and especially manipulating atomic motion, enabling atom-by-atom fabrication. These applications, as well as traditional imaging of beam sensitive materials, necessitate increasing the dynamic range of STEM in imaging and manipulation modes, and increasing the absolute scanning speed which can be achieved by combining sparse sensing methods with nonrectangular scanning trajectories. We have developed a general method for real-time reconstruction of sparsely sampled images from high-speed, noninvasive and diverse scanning pathways, including spiral scan and Lissajous scan. This approach is demonstrated on both the synthetic data and experimental STEM data on the beam sensitive material graphene. This work opens the door for comprehensive investigation and optimal design of dose efficient scanning strategies and real-time adaptive inference and control of e-beam induced atomic fabrication.

47 OTHER INSTRUMENTATION↗

Dynamic Modeling and Simulation of a Subcritical Coal-Fired Power Plant under Load-Following Conditions

Dynamic models for power plants that capture realistic general process trends and effects of manipulated variables are needed to improve load-following, while minimizing carbon footprint. In this work, a dynamic modeling approach and simulation results for subcritical coal-fired power plant components are presented. These encompass simulation of the dynamics in the fireside, including the effects of fuel, air combustion, and the dynamics of the entire waterside and power generation sections. This model development enables the simulation and analysis of the important short and long-time scale dynamics of components such as heaters, evaporative loop, and power generation units. Furthermore, additional variables in the power generation section are introduced to improve model accuracy, extending the prediction capability of subcritical power plant models and opening new opportunities for research in operator training, optimization, and advanced model-based controller design that are based on these models. The change in process gain for different ramp rates associated with disturbance signals that affect process variables is also explored and a correlation developed. This provides opportunities to study disturbance rejection control implementation and adaptation for scenarios with such variations in ramp rates. The prediction capabilities of selected components are compared to data available in literature, with the obtained root mean squared error ranges that reflect the model performance and quality of predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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