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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.

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At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Adaptive precompensators for flexible-link manipulator control

The application of input precompensators to flexible manipulators is considered. Frequency domain compensators color the input around the flexible mode locations, resulting in a bandstop or notch filter in cascade with the system. Time domain compensators apply a sequence of impulses at prespecified times related to the modal frequencies. The resulting control corresponds to a feedforward term that convolves in real-time the desired reference input with a sequence of impulses and produces a vibration-free output. An adaptive precompensator can be implemented by combining a frequency domain identification scheme which is used to estimate online the modal frequencies and subsequently update the bandstop interval or the spacing between the impulses. The combined adaptive input preshaping scheme provides the most rapid slew that results in a vibration-free output. Experimental results are presented to verify the results.

Tzes, Anthony P.↗
NASA NTRS1982

A temperature control design for a tapered element oscillating microbalance sensing surface

A design study is presented which shows that a tapered element oscillating microbalance can be adapted for temperature control under space application by mating with multistage thermoelectric coolers in such a way that an integral structure evolves. The control of the temperature of the sensing surface can be achieved in a number of ways. An indirect method which uses a measurement of the absorbed power is recommended. The design goals can be met if a relaxation of the power requirement can be considered.

Source record↗
NASA NTRS2004

Learning to Control Advanced Life Support Systems

Advanced life support systems have many interacting processes and limited resources. Controlling and optimizing advanced life support systems presents unique challenges. In particular, advanced life support systems are nonlinear coupled dynamical systems and it is difficult for humans to take all interactions into account to design an effective control strategy. In this project. we developed several reinforcement learning controllers that actively explore the space of possible control strategies, guided by rewards from a user specified long term objective function. We evaluated these controllers using a discrete event simulation of an advanced life support system. This simulation, called BioSim, designed by Nasa scientists David Kortenkamp and Scott Bell has multiple, interacting life support modules including crew, food production, air revitalization, water recovery, solid waste incineration and power. They are implemented in a consumer/producer relationship in which certain modules produce resources that are consumed by other modules. Stores hold resources between modules. Control of this simulation is via adjusting flows of resources between modules and into/out of stores. We developed adaptive algorithms that control the flow of resources in BioSim. Our learning algorithms discovered several ingenious strategies for maximizing mission length by controlling the air and water recycling systems as well as crop planting schedules. By exploiting non-linearities in the overall system dynamics, the learned controllers easily out- performed controllers written by human experts. In sum, we accomplished three goals. We (1) developed foundations for learning models of coupled dynamical systems by active exploration of the state space, (2) developed and tested algorithms that learn to efficiently control air and water recycling processes as well as crop scheduling in Biosim, and (3) developed an understanding of the role machine learning in designing control systems for advanced life support.

Subramanian, Devika↗
NASA NTRS1992

A neural fuzzy controller learning by fuzzy error propagation

In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.

Nauck, Detlef↗
DOE OSTI2022

Implementation of a Model Predictive Control Strategy to Regulate Temperature Inside Plug-Flow Solar Reactor With Countercurrent Flow

Abstract Solar-driven thermochemical energy storage systems are proven to be promising energy carriers (solar fuels) to utilize solar energy by using reactive solid-state pellets. However, the production of solar fuel requires a quasi-steady-state process temperature, which represents the main challenge due to the transient nature of solar power. In this work, an adaptive model predictive controller (MPC) is presented to regulate the temperature inside a tubular solar reactor to produce solid-state solar fuel for long-term thermal storage systems. The solar reactor system consists of a vertical tube heated circumferentially over a segment of its length by concentrated solar power, and the reactive pellets (MgMn2O4) are fed from the top end and flow downwards through the heated tube. A countercurrent flowing gas supplied from the lower end interacts with flowing pellets to reduce it thermochemically at a temperature range of 1000—1500 °C. A low-order physical model was developed to simulate the dynamics of the solar reactor including the reaction kinetics, and the proposed model was validated numerically by using a 7-kW electric furnace. The numerical model then was utilized to design the MPC controller, where the control system consists of an MPC code linked to an adaptive system identification code that updates system parameters online to ensure system robustness against external disturbances (sudden change in the flow inside the reactor), model mismatches, and uncertainty. The MPC controller parameters are tuned to enhance the system performance with minimum steady-state error and overshoot. The controller is tested to track different temperature ranges between 500 °C and 1400 °C with different particles/gas mass flowrates and ramping temperature profiles. Results show that the MPC controller successfully regulated the reactor temperature within ± 1 °C of its setpoint and maintained robust performance with minimum input effort when subjected to sudden changes in the amount of flowing media and the presence of chemical reaction.

Engineering↗
DOE OSTI2019

Hygrothermal analyses of the moisture control and energy efficiency potential of an adaptive water-resistive barrier for building envelopes

A water-resistive barrier (WRB) is a material installed on the exterior side of the sheathing to prevent water intrusion so that building components are not damaged by moisture. A membrane that can change its water vapor permeability between two states to control water vapor transport into and out of residential and commercial building wall systems is being developed. This simulation study assesses if this membrane used as a WRB reduces moisture levels and mold growth risk in exterior walls and building energy consumption. The developed membrane may require modifications to fully function as a WRB in contact with liquid water. Hygrothermal component simulations were conducted for different climate zones, different wall assemblies, different switching points and permeabilities to identify the most beneficial application cases and their required perm range and switching control. The study details the required simulation settings and suggests that the switchable membrane can reduce the water content in the sheathing and reduce the mold growth risk in the cavity in all climate zones. The effect on energy consumption of the switchable membrane is not significant. The study also includes recommendations on how to model the material characteristics of a switchable membrane and recommendations on practical applications for the switchable membrane.

42 ENGINEERING↗
DOE OSTI2020

Value Gradient Learning Approach in Power and Frequency Regulation of Grid-Connected Synchronverters

In this paper, a neural network adaptive critic design (ACD) method based on value gradient learning (VGL) is used to optimally control a grid-connected synchronverter. The main drawback of the traditional synchronverters is their infeasibility to face non-inductive grids. To be able to implement a synchronverter technique in any impedance angle, a neural network-based adaptive controller is used. The advantage of adaptive dynamic programing is its ability to adjust itself when it faces changes and uncertainties in the power system. The proposed VGL consists of two subnetworks: the critic network and the action network. The action network is trained during the operation, and the critic network can be pretrained offline or can be simultaneously trained with the action network. To compare the effectiveness of the traditional synchronverter to the VGL-based synchronverter, the simulation results are provided.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1985

Measuring Absolute Oxygen Pressure

Sensor determines absolute pressure of oxygen without reference pressure source. Absolute oxygen pressure transducer with control circuit enables measurement without reference pressure. Transducer, two part device, combines solid electrolyte membranes sensor with diffusional orifice. Device adapted for direct control of oxygen pressure in combustion mixtures.

Richter, R.↗
NASA NTRS1988

Generic supervisor: A knowledge-based tool for control of space station on-board systems

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.

Carnes, J. R.↗
NASA NTRS1989

Global models: Robot sensing, control, and sensory-motor skills

Robotics research has begun to address the modeling and implementation of a wide variety of unstructured tasks. Examples include automated navigation, platform servicing, custom fabrication and repair, deployment and recovery, and science exploration. Such tasks are poorly described at onset; the workspace layout is partially unfamiliar, and the task control sequence is only qualitatively characterized. The robot must model the workspace, plan detailed physical actions from qualitative goals, and adapt its instantaneous control regimes to unpredicted events. Developing robust representations and computational approaches for these sensing, planning, and control functions is a major challenge. The underlying domain constraints are very general, and seem to offer little guidance for well-bounded approximation of object shape and motion, manipulation postures and trajectories, and the like. This generalized modeling problem is discussed, with an emphasis on the role of sensing. It is also discussed that unstructured tasks often have, in fact, a high degree of underlying physical symmetry, and such implicit knowledge should be drawn on to model task performance strategies in a methodological fashion. A group-theoretic decomposition of the workspace organization, task goals, and their admissible interactions are proposed. This group-mechanical approach to task representation helps to clarify the functional interplay of perception and control, in essence, describing what perception is specifically for, versus how it is generically modeled. One also gains insight how perception might logically evolve in response to needs of more complex motor skills. It is discussed why, of the many solutions that are often mathematically admissible to a given sensory motor-coordination problem, one may be preferred over others.

Schenker, Paul S.↗
NASA NTRS1974

Modern control concepts in hydrology

Two approaches to an identification problem in hydrology are presented based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time invariant or time dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and conform with results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second, by using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

Duong, N.↗
NASA NTRS1975

Modern control concepts in hydrology

Two approaches to an identification problem in hydrology are presented, based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time-invariant or time-dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and confirm the results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

Duong, N.↗
DOE OSTI2020

Leveraging Fine-Grained Occupancy Estimation Patterns for Effective HVAC Control

As occupancy sensing technologies become mature, various occupancy sensors are increasingly deployed in commercial buildings for pervasive occupancy monitoring. These sensors provide occupant-count data, which contains rich spatiotemporal information about occupancy patterns. With long-term occupant-count data collected from a commercial building, we design three different predictive models that capture the occupancy dynamics and examine how a model predictive control of the HVAC system benefits from actual occupancy count prediction. Our analysis reveals that mispredictions of occupancy states, especially false positives and false negatives, may introduce inefficient control that leads to energy waste or user discomfort. To address this issue, we take a step further to design an adaptive model predictive controller that minimizes inefficient control actions according to misprediction types and distributions. A comprehensive evaluation is performed in OpenBuild and EnergyPlus simulators to study the effectiveness of the proposed end-to-end control strategy. The evaluation shows that the proposed solution reduces energy consumption by 29.5% while improving the average weighted occupants comfort by 86.7% in Predicted Mean Vote (PMV) over the fixed schedule strategy.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

Adaptive planning for applications with dynamic objectives

We devise a qualitative control layer to be integrated into a real-time multi-agent reactive planner. The reactive planning system consists of distributed planning agents attending to various perspectives of the task environment. Each perspective corresponds to an objective. The set of objectives considered are sometimes in conflict with each other. Each agent receives information about events as they occur, and a set of actions based on heuristics can be taken by the agents. Within the qualitative control scheme, we use a set of qualitative feature vectors to describe the effects of applying actions. A qualitative transition vector is used to denote the qualitative distance between the current state and the target state. We will then apply on-line learning at the qualitative control level to achieve adaptive planning. Our goal is to design a mechanism to refine the heuristics used by the reactive planner every time an action is taken toward achieving the objectives, using feedback from the results of the actions. When the outcome is compared with expectations, our prior objectives may be modified and a new set of objectives (or a new assessment of the relative importance of the different objectives) can be introduced. Because we are able to obtain better estimates of the time-varying objectives, the reactive strategies can be improved and better prediction can be achieved.

Hadavi, Khosrow↗
NASA NTRS1995

An Electronic Workshop on the Performance Seeking Control and Propulsion Controlled Aircraft Results of the F-15 Highly Integrated Digital Electronic Control Flight Research Program

Flight research for the F-15 HIDEC (Highly Integrated Digital Electronic Control) program was completed at NASA Dryden Flight Research Center in the fall of 1993. The flight research conducted during the last two years of the HIDEC program included two principal experiments: (1) performance seeking control (PSC), an adaptive, real-time, on-board optimization of engine, inlet, and horizontal tail position on the F-15; and (2) propulsion controlled aircraft (PCA), an augmented flight control system developed for landings as well as up-and-away flight that used only engine thrust (flight controls locked) for flight control. In September 1994, the background details and results of the PSC and PCA experiments were presented in an electronic workshop, accessible through the Dryden World Wide Web (http://www.dfrc.nasa.gov/dryden.html) and as a compact disk.

Powers, Sheryll Goecke↗
NASA NTRS1989

Control of a slow moving space crane as an adaptive structure

Assuming that the space crane is an adaptive structure with length-adjustable bars and taking as controls the length-adjustments of these bars, the computation of the incremental controls corresponding to the motion of a payload along its minimum-energy trajectory is given in terms of the inverse-transpose of matrix B of the joint equilibrium equations Bs = p, where s lists the bar forces and p lists the nodal loads. The compensation of the controls for elastic deformations and support movements are shown. It is also shown that the computations may be done automatically and in real time by an attached processor once the characteristics of the crane's maneuver are keyed in.

Utku, S.↗
NASA NTRS2010

Vestibular-Somatosensory Convergence in Head Movement Control During Locomotion after Long-Duration Space Flight

Exposure to the microgravity conditions of space flight induces adaptive modification in the control of vestibular-mediated reflexive head movement during locomotion after space flight. Space flight causes astronauts to be exposed to somatosensory adaptation in both the vestibular and body load-sensing (BLS) systems. The goal of these studies was to examine the contributions of vestibular and BLS-mediated somatosensory influences on head movement control during locomotion after long-duration space flight. Subjects were asked to walk on a treadmill driven at 1.8 m/s while performing a visual acuity task. Data were collected using the same testing protocol from three independent subject groups; 1) normal subjects before and after exposure to 30 minutes of 40% bodyweight unloaded treadmill walking, 2) bilateral labyrinthine deficient (LD) patients and 3) astronauts who performed the protocol before and after long duration space flight. Motion data from head and trunk segmental motion data were obtained to calculate the angular head pitch (HP) movements during walking trials while subjects performed the visual task, to estimate the contributions of vestibular reflexive mechanisms in HP movements. Results showed that exposure to unloaded locomotion caused a significant increase in HP movements, whereas in the LD patients the HP movements were significantly decreased. Astronaut subjects results showed a heterogeneous response of both increases and decreases in the amplitude of HP movement. We infer that BLS-mediated somatosensory input centrally modulates vestibular input and can adaptively modify head-movement control during locomotion. Thus, space flight may cause a central adaptation mediated by the converging vestibular and body load-sensing somatosensory systems.

Mulavara, Ajitkumar↗