SEARCH · Engineering Papers

Results for “Hierarchical control”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Fibrous anisotropy and mineral gradients within the radula stylus of chiton: Controlled stiffness and damage tolerance in a flexible biological composite

Over hundreds of millions of years, organisms have evolved architected structures via precise control over hierarchically assembled components, including the integration of dissimilar materials. One such example is found in the radula system of chitons, intertidal mollusks that feed on algae growing on the rock. Their radula consists of multiple rows of ultrahard teeth, each integrated with a foldable belt-like substrate via a stiff, yet flexible stylus, which is essential for efficient rasping during the feeding process. Here, we investigate the nano and micro-scale components and architectures as well as regional mechanical properties of the stylus, and their subsequent role during the rasping of Cryptochiton stelleri. Three important factors were determined to contribute to the regio-specific stiffness of the stylus: the presence of mineral components, highly oriented chitinous fibers, and a chemically cross-linked protein matrix. All these factors are varied throughout the stylus. There is a high mineral content on the trailing edge close to the tooth and a cross-linked matrix on the leading edge, both with orientational specific oriented chitin fibers that provide force transduction to the tooth. Conversely, there is a significant lack of mineral or cross-linked matrix in the proximal end as well as a low degree of fiber orientation, resulting in a flexible region that can accommodate torsion and flexure during rasping. Understanding the graded composite structure of the stylus and applying this unique design to various engineering fields such as soft robotics, biotechnology, and the medical industry, can inspire the production of high-performance materials.

Lee, Jung-Eun↗

DOE OSTI2024

Controlling reversible phase transitions in rare-earth nickelates for novel memory devices

Resistive switching in correlated complex oxides is lucrative for emerging applications in neuromorphic computing, and densely scaled non-volatile memory. Electrical conductance of such complex oxides can be controllable switched across multiple orders of magnitude by either (a) electroforming a conduction channel (e.g., in tungsten oxide), or (b) inducing Mott-Hubbard transition (e.g., in rare-earth nickelates)– both via controlled migration of defects (such as oxygen vacancies) under applied bias. Nevertheless, the promise of such defect-driven electronic transitions are far from realized due to a lack of fundamental understanding of the atomic-scale processes that underlie migration and spatiotemporal evolution of oxygen vacancies over nano-to-mesoscopic length/timescales under applied electric field. In this project, we employ a synergistic integration of density functional theory (DFT) calculations, ab initio/classical molecular dynamics (AIMD/CMD) simulations, machine learning (ML), precision synthesis, and multi-modal X-ray imaging experiments to address this knowledge gap. Such an integrated approach offers to elucidate the correlations between subtle structural distortion and oxidation states; treat localized charge carriers; describe defect/ion transport in the presence of electric field; and, in turn, greatly advance the current understanding of microstructural evolution in complex oxides under applied bias. The fundamental knowledge gained from this work will enable precise control over hierarchical defect structures and unravel new routes to manipulate resistance states in complex oxides. This, in turn, will accelerate design of novel devices with desired set of neural functionalities, and high-speed densely-scaled resistive random access memory technologies.

36 MATERIALS SCIENCE↗

NASA NTRS1975

Problems, questions and results in the use of the BBN-model

A hierarchical structured control model was used to describe pilot performance in a multivariable control problem. The model is based on the assumption that a well trained operator optimized a quadratic optimization criterion. The model considers some special characteristics of the human operator as time delay, neuromuscular time lag, observation and motor noise and the ability to extract the first derivative of a displaced value. Numerical results of a simple human engineering example using the BBN model demonstrate the influence of the variation of different parameters on covariance matrices of the state and observation vectors.

Dey, D.↗

NASA NTRS1989

A Boltzmann machine for the organization of intelligent machines

In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved to converge to the minimum of a cost function. Finally, simulations will show the effectiveness of a variety of search techniques for the intelligent machine.

Moed, Michael C.↗

NASA NTRS1989

Design and control of a multi-fingered robot hand provided with tactile feedback

The design, construction, control and application of a three fingered robot hand with nine degrees of freedom and built-in multi-component force sensors is described. The adopted gripper kinematics are justified and optimized with respect to grasping and manipulation flexibility. The hand was constructed with miniature motor drive systems imbedded into the fingers. The control is hierarchically structured and is implemented on a simple PC-AT computer. The hand's dexterity and intelligence are demonstrated with some experiments.

Vanbrussel, H.↗

NASA NTRS1990

A Boltzmann machine for the organization of intelligent machines

A three-tier structure consisting of organization, coordination, and execution levels forms the architecture of an intelligent machine using the principle of increasing precision with decreasing intelligence from a hierarchically intelligent control. This system has been formulated as a probabilistic model, where uncertainty and imprecision can be expressed in terms of entropies. The optimal strategy for decision planning and task execution can be found by minimizing the total entropy in the system. The focus is on the design of the organization level as a Boltzmann machine. Since this level is responsible for planning the actions of the machine, the Boltzmann machine is reformulated to use entropy as the cost function to be minimized. Simulated annealing, expanding subinterval random search, and the genetic algorithm are presented as search techniques to efficiently find the desired action sequence and illustrated with numerical examples.

Moed, Michael C.↗

NASA NTRS1989

Structures cluster

The objective of this program is to develop technology needed for structural evaluation of alternative space construction concepts. Those concepts are as follows: interactive effects on dynamic performance of various environment and self-generated disturbance; new materials concepts, failure mechanisms, and non-destructive evaluation/failure detection; develop stable control algorithms and design effective combination of hierarchical and adaptive controls; and assess control-structure integrated performance and stability.

Datta, Subhendu K.↗

DOE OSTI2022

Control over emergence and alignment of transient blisters in thermo-responsive gels using hierarchically patterned substrates

Surfaces with tunable microscale textures are vital in a large variety of technological applications, including heat transfer, antifouling and adhesion. To facilitate such broad-scale use, there is a need to create surfaces that undergo reconfigurable changes in topology and thus, enable switchable functionality. To date, there is a relative dearth of methods for engineering surfaces that can be actuated to change topography over a range of length scales, and hence, form tunable hierarchically structured layers. Combining modeling and experiments, we design a geometrically patterned, thermo-responsive poly (N-isopropylacrylamide) gel film that undergoes controllable hierarchical changes in topology with changes in temperature. At the bottom, the film is covalently bound to a solid, curved substrate; at the top, the film encompasses longitudinal rectangular ridges that are oriented perpendicular to the underlying cylindrical curves. At temperatures below lower critical solution temperature (LCST), the swollen gel exhibits 3D variations in polymer density and thickness defined by the gel's top and bottom topography. As the temperature rises above LCST, the interplay between the upper ridges and lower curves in the gel drives non-uniform, directional solvent transport, the nucleation and propagation of a phase-separated higher-density skin layer, and the resulting pressure buildup within the film. These different, interacting kinetic processes lead to an instability, which produces transient microscopic blisters in the film. Through simulations, we show how tuning the width of the ridges modifies the propagation of a skin layer and creates localized pressure build-up points, which enables control over the emergence, distribution, and alignment of the microscopic blisters. Futhermore, we provide a simple argument to predict the size of such microscopic features. Experiments confirm our predictions and further highlight how our computational model enables the rational design of topographical transitions in these tunable films. The development of actuatable, hierarchically structured films provides new routes for achieving switchable functionality in actuators, drug release systems and adhesives.

42 ENGINEERING↗

DOE OSTI2025

Multi-Agent Hierarchical Deep Reinforcement Learning for HVAC Control With Flexible DERs

As electricity consumption in commercial and residential buildings continues to rise, reducing energy costs presents an increasing challenge. Heating, ventilating, and air-conditioning (HVAC) systems, which typically account for 40%-50% of a building's energy use, are prime targets for energy savings. Intelligent control of HVAC temperature through the exploitation of HVAC load flexibility brings significant potential to reduce energy consumption and electricity expenses. The nonlinear models of HVAC systems challenge traditional control methods, while the uncertainty introduced by HVAC load flexibility complicates distributed energy resource (DER) management using conventional optimal dispatch techniques. In response to these challenges, we propose a hierarchical multi-agent deep reinforcement learning (DRL) approach. The lower-level agents focus on balancing comfort and energy conservation, while the upper-level DRL agents optimize the use of DERs to reduce peak demand based on the control outcomes of the HVAC by the lower-level agents. Here, in the upper-level agents, we incorporate a multi-agent structure based on ensemble learning, which acts based on historical and current data without relying on precise load forecasting to address the delayed rewarding issue in DRL. This allows for the effective reduction of energy costs. The proposed method is tested using a real-world microgrid comprising 413 buildings in Southern California, and the results demonstrate that our approach can significantly reduce overall electricity bills while ensuring the comfort of consumers and residents.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Chemically Controllable Porous Polymer–Nanocrystal Composites with Hierarchical Arrangement Show Substrate Transport Selectivity

Functional organic–inorganic hybrid materials with tunable properties are useful across many application areas, ranging from gas storage to electronics, flame retardants, separations, and catalysis. Combining polymers, with a suite of functional groups and conformational flexibility, and inorganic nanoparticles, with tunable surface chemistry and composition, yields hybrids with novel functional properties. Specifically, in catalysis, control of the electronic environment at a metal interface is paramount in determining the catalytic properties. In this contribution, we describe a modular process to prepare porous polymer–nanocrystal (NC) composites in a hierarchical, multilayered synthesis, in which multiple parameters can be accurately tuned: polymer functional groups and the corresponding pore structure, the polymer layer thickness, and the NC size, shape, and composition. This process provides for a variety of controlled materials with high surface area, tunable chemistry, and thermal and chemical stabilities. Furthermore, we demonstrate their utility for shape- and size-selective catalytic conversions both in oxidation and hydrogenation reactions, where they show increased selectivity by orders of magnitude compared to conventional polymer-supported metal catalysts. In light of the high degree of control in the composite structure, this method allows for the design and realization of catalysts for several reactions and reaction environments and for nanomaterials with other applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1992

More About Architecture For Intelligent Robotic Control

Boolean neural networks proposed to implement part of intermediate level of hierarchical architecture of control system for artificially intelligent control of robot hand. Concept described in "Architecture for Intelligent Control of Robotic Tasks" (NPO-17871). Rule level of architecture implemented in two Boolean neural networks operated and updated in alternation. No explicit programming of network. Internal configuration not unique but, depends on initial state and history of previous adaptations. Accepts new rules sequentially presented by external controller.

Fiorini, Paolo↗

NASA NTRS1992

Description of the SSF PMAD DC testbed control system data acquisition function

The NASA LeRC in Cleveland, Ohio has completed the development and integration of a Power Management and Distribution (PMAD) DC Testbed. This testbed is a reduced scale representation of the end to end, sources to loads, Space Station Freedom Electrical Power System (SSF EPS). This unique facility is being used to demonstrate DC power generation and distribution, power management and control, and system operation techniques considered to be prime candidates for the Space Station Freedom. A key capability of the testbed is its ability to be configured to address system level issues in support of critical SSF program design milestones. Electrical power system control and operation issues like source control, source regulation, system fault protection, end-to-end system stability, health monitoring, resource allocation, and resource management are being evaluated in the testbed. The SSF EPS control functional allocation between on-board computers and ground based systems is evolving. Initially, ground based systems will perform the bulk of power system control and operation. The EPS control system is required to continuously monitor and determine the current state of the power system. The DC Testbed Control System consists of standard controllers arranged in a hierarchical and distributed architecture. These controllers provide all the monitoring and control functions for the DC Testbed Electrical Power System. Higher level controllers include the Power Management Controller, Load Management Controller, Operator Interface System, and a network of computer systems that perform some of the SSF Ground based Control Center Operation. The lower level controllers include Main Bus Switch Controllers and Photovoltaic Controllers. Power system status information is periodically provided to the higher level controllers to perform system control and operation. The data acquisition function of the control system is distributed among the various levels of the hierarchy. Data requirements are dictated by the control system algorithms being implemented at each level. A functional description of the various levels of the testbed control system architecture, the data acquisition function, and the status of its implementationis presented.

Baez, Anastacio N.↗

NASA NTRSDate not supplied

SUSAN Power/Propulsion System Emulation Test Predictions

The development of all-electric and hybrid-electric propulsion systems for transport aircraft presents an opportunity for new designs that can reduce fuel consumption and emissions from commercial aviation while enabling safer and more reliable aircraft. The SUbsonic Single Aft eNgine (SUSAN) is a conceptual design for a single-aisle transport aircraft with a series/parallel partial-hybrid propulsion system that is being developed by NASA as a reference design for single-aisle transport with a high degree of electrification. The SUSAN aircraft incorporates multiple tightly coupled power, propulsion, and flight control systems. This coupling leads to challenges in the aircraft control design process, requiring a hierarchical and more coordinated control architecture. This presentation will summarize the plans for a Hardware-in-the-Loop (HIL) test performed in the Hybrid Propulsion Emulation Rig (HyPER) facility at NASA Glenn Research Center (GRC). During this test, a real-time reference model of the full-scale SUSAN powertrain and controllers will be run alongside a sub-scale electro-mechanical system representing a portion of the electrified components in the SUSAN hybrid powertrain. This test will allow the performance of the SUSAN controllers to be evaluated using real powertrain components and allows side-by-side comparison between the real and modeled subsystems. This presentation will summarize the full-scale system model, steps towards integration of representative hardware for future control testing, and predicted results.

Jonah J. Sachs-Wetstone↗

NASA NTRS2024

SUbsonic Single Aft eNgine (SUSAN) Power/Propulsion System Control Architecture Updates

The development of hybrid-electric propulsion technology for transport aircraft presents opportunities for new designs that can reduce fuel consumption and greenhouse gas emissions from commercial aviation and improve on safety and reliability when compared to modern aircraft. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a conceptual design for a transport aircraft with a series/parallel partial hybrid-electric propulsion system that is being developed by NASA as a reference design for a regional transport aircraft with a high degree of electrification. The SUSAN concept incorporates multiple tightly coupled power, propulsion, and flight control systems that introduce new challenges to the control design process, requiring a hierarchical and more coordinated control architecture. This paper summarizes updates to the SUSAN Power/Propulsion System (PPS) model and control architecture made in preparation for planned flight simulator and hardware-in-the-loop testing at NASA Glenn Research Center (GRC). These updates include a new electrical power system (EPS) model based on the NASA-developed Electrical Modeling and Thermal Analysis Toolbox (EMTAT), and a new PPS control architecture that improves the operational flexibility and responsiveness of the propulsion system. The performance of the upgraded control system is also demonstrated and discussed.

SUSAN↗

NASA NTRS2024

SUbsonic Single Aft eNgine (SUSAN) Power/Propulsion System Control Architecture Updates

The development of hybrid-electric propulsion technology for commercial transport aircraft presents opportunities for new designs that can reduce fuel consumption and greenhouse gas emissions and improve safety and reliability compared to modern aircraft. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a conceptual design for a transport aircraft with a series/parallel partial hybrid-electric propulsion system being developed by NASA as a reference design for a regional transport aircraft with a high degree of electrification. The SUSAN concept incorporates multiple tightly coupled power, propulsion, and flight control systems that introduce new challenges to the control design process, requiring a hierarchical and more coordinated control approach. This report summarizes updates to the SUSAN power/propulsion system (PPS) model and control architecture made in preparation for planned flight simulator and hardware-in-the-loop testing at the NASA Glenn Research Center. These updates include a new electrical power system model developed using the NASA-developed Electrical Modeling and Thermal Analysis Toolbox (EMTAT) and a new PPS control architecture that improves the operational flexibility and responsiveness of the propulsion system. The performance of the updated controller is demonstrated and discussed.

SUSAN↗

NASA NTRS2024

SUbsonic Single Aft eNgine (SUSAN) Power/Propulsion System Control Architecture Updates

SUSAN↗

DOE OSTI2026

Compositional Reasoning for Hierarchical State Machines

Harel statecharts and its derivatives are popular graphical languages for specifying discrete control systems via hierarchical state machines. Separately, there has been a long line of work on specifying concurrent systems with process calculi which come equipped with an algebraic theory, the ability reason compositionally about various temporal properties, and strong type systems. While these two approaches to modeling systems are tantalizingly similar, the integrated reasoning principles that exist for process calculi have not been demonstrated in hierarchical state machines. A key issue is that operational theories for process calculi do not behave like control systems, and thus, there is virtually no tool support for modeling control systems with such languages. For a control system designer, bringing the integrated, more scalable reasoning from the process calculi to state-machine languages would enable the specification of more complex systems and a more modular systems development process. Our insight is that we can recover many important results from the process calculi in hierarchical state machines with local scope. We employ a structural operational semantics, which is ubiquitous in process and 𝜆-calculi but uncommon in hierarchical statemachine formalizations, to enable inductive reasoning about behavior. Taking inspiration from the structure of process calculi metatheories, we define a calculus of refinement and equivalence that we prove sound with respect to local notion of (bi)simulation. Furthermore, we prove that the calculus preserves the behavioral properties of reactivity, observational determinism, traces, and linear temporal properties. Our results are mechanized in the Rocq proof assistant.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2016

Community Involvement in Enhancing the Global Change Master Directory (GCMD) Controlled Vocabularies (Keywords)

NASA's Global Change Master Directory (GCMD) develops and expands a hierarchical set of controlled vocabularies (keywords) covering the Earth sciences and associated information (data centers, projects, platforms, instruments, etc.). The purpose of the keywords is to describe Earth science data and services in a consistent and comprehensive manner, allowing for the precise searching of metadata and subsequent retrieval of data and services. The keywords are accessible in a standardized SKOSRDFOWL representation and are used as an authoritative taxonomy, as a source for developing ontologies, and to search and access Earth Science data within online metadata catalogues. The keyword development approach involves: (1) receiving community suggestions, (2) triaging community suggestions, (3) evaluating the keywords against a set of criteria coordinated by the NASA ESDIS Standards Office, and (4) publication/notification of the keyword changes. This approach emphasizes community input, which helps ensure a high quality, normalized, and relevant keyword structure that will evolve with users changing needs. The Keyword Community Forum, which promotes a responsive, open, and transparent processes, is an area where users can discuss keyword topics and make suggestions for new keywords. The formalized approach could potentially be used as a model for keyword development.

governance↗