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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Adaptive Online Model Update Algorithm for Predictive Control in Networked Systems

In this article, we introduce an adaptive on-line model update algorithm designed for predictive control applications in networked systems, particularly focusing on power distribution systems. Unlike traditional methods that depend on historical data for offline model identification, our approach utilizes real-time data for continuous model updates. This method integrates seamlessly with existing online control and optimization algorithms and provides timely updates in response to real-time changes. This methodology offers significant advantages, including a reduction in the communication network bandwidth requirements by minimizing the data exchanged at each iteration and enabling the model to adapt after disturbances. Furthermore, our algorithm is tailored for non-linear convex models, enhancing its applicability to practical scenarios. The efficacy of the proposed method is validated through a numerical study, demonstrating improved control performance using a synthetic IEEE test case.

data-driven model predictive control↗
DOE OSTI2022

Decentralized modular hybrid supervisory control for the formation of unmanned helicopters

Abstract Formation control of Unmanned Aerial Vehicles (UAVs) requires them to tightly cooperate to reach and keep the formation, while avoiding collision. This paper proposes a novel decentralized hybrid supervisory control approach for the formation control of multiple UAVs. This is achieved by developing a symbolic motion planning technique to polarly partition the motion space resulting in a finite state discrete event model for the motion dynamics of each UAV. Then, a modular discrete supervisor is designed for different components of the formation mission including reaching the formation, keeping the formation, and collision avoidance. Further, for the collision avoidance mechanism, a novel top‐down decomposition‐based approach is developed to design local supervisors decentralizedly. It is formally proved that with the proposed top‐down decomposition‐based approach, the (locally) supervised UAVs, as a whole, can cooperatively satisfy the desired (global) collision avoidance specification. The proposed decentralized supervisory control algorithm is also verified through a hardware‐in‐the‐loop simulator for the formation control of unmanned helicopters.

Karimoddini, Ali↗
DOE OSTI2021

Event-Driven Predictive Approach for Real-Time Volt/VAR control with CVR in solar PV rich Active Distribution Network

The focus of this paper is on analyzing the impact of conservation voltage reduction in the presence of active devices such as solar photovoltaic (PV) and developing controls that leverage these distributed energy resources. An event-driven predictive approach for real-time volt/volt-ampere reactive (VAR) optimization, along with local two-level adaptive volt/VAR droop-based control algorithm for advanced distribution management systems, is introduced. The methodology covers aggregated and autonomous controls under different timescale operations, including the impact and effect of unpredicted events such as cloud transients on PV power production. In addition, the control schemes include the uncertainties in PV power generation and load power demand. The proposed methodology is validated in a real-time framework using the real-time digital simulator platform through co-simulation with models based on Python and OpenDSS (Open Distribution System Simulator). The developed methodology is tested on the modified IEEE 123-feeder test system. The results reveal that the proposed methodology works well in the presence of high penetrations of PV power, produces significant energy savings, and mitigates over-/undervoltage problems.

14 SOLAR ENERGY↗
DOE OSTI2025

Learning error distribution kernel‐enhanced neural network methodology for multi‐intersection signal control optimization

Traffic congestion has substantially induced significant mobility and energy inefficiency. Many research challenges are identified in traffic signal control and management associated with artificial intelligence (AI)-based models. For example, developing AI-driven dynamic traffic system models that accurately capture high-resolution traffic attributes and formulate robust control algorithms for traffic signal optimization is difficult. Additionally, uncertainties in traffic system modeling and control processes can further complicate traffic signal system controllability. To partially address these challenges, this study presents a novel, hybrid neural network model enhanced with a probability density function kernel shaping technique to formulate traffic system dynamics better and improve comprehensive traffic network modeling and control. The numerical experimental tests were conducted, and the results demonstrate that the proposed control approach outperforms the baseline control strategies and reduces overall average delays by 11.64% on average. By leveraging the capabilities of this innovative model, this study aims to address major challenges related to traffic congestion and energy inefficiency toward more effective and adaptable AI-based traffic control systems.

Wang, Hong [Oak Ridge National Laboratory (ORNL), ↗
NASA NTRS1973

Digital adaptive flight controller development

The development of a digital adaptive flight control algorithm is described that combines a weighted least squares estimator with optimal linear regulator control logic designed to minimize a quadratic model following performance index. Very promising results for a typical fighter aircraft's trajectory over six distinct flight conditions are reported.

Kaufman, H.↗
NASA NTRS1987

User guide for the digital control system of the NASA/Langley Research Center's 13-inch Magnetic Suspension and Balance System

The technical background to the development of the digital control system of the NASA/Langley Research Center's 13 inch Magnetic Supension and Balance Systen (MSBS) is reviewed. The implementation of traditional MSBS control algorithms in digital form is examined. Extensive details of the 13-inch MSBS digital controller and related hardware are given, together with the introductory instructions for systems operators. Full listings of software are included in the Appendices.

Britcher, Colin P.↗
NASA NTRS1988

Effects of computing time delay on real-time control systems

The reliability of a real-time digital control system depends not only on the reliability of the hardware and software used, but also on the speed in executing control algorithms. The latter is due to the negative effects of computing time delay on control system performance. For a given sampling interval, the effects of computing time delay are classified into the delay problem and the loss problem. Analysis of these two problems is presented as a means of evaluating real-time control systems. As an example, both the self-tuning predicted (STP) control and Proportional-Integral-Derivative (PID) control are applied to the problem of tracking robot trajectories, and their respective effects of computing time delay on control performance are comparatively evaluated. For this example, the STP (PID) controller is shown to outperform the PID (STP) controller in coping with the delay (loss) problem.

Shin, Kang G.↗
NASA NTRS2011

Implementation of Enhanced Propulsion Control Modes for Emergency Flight Operation

Aircraft engines can be effective actuators to help pilots avert or recover from emergency situations. Emergency control modes are being developed to enhance the engines performance to increase the probability of recovery under these circumstances. This paper discusses a proposed implementation of an architecture that requests emergency propulsion control modes, allowing the engines to deliver additional performance in emergency situations while still ensuring a specified safety level. In order to determine the appropriate level of engine performance enhancement, information regarding the current emergency scenario (including severity) and current engine health must be known. This enables the engine to operate beyond its nominal range while minimizing overall risk to the aircraft. In this architecture, the flight controller is responsible for determining the severity of the event and the level of engine risk that is acceptable, while the engine controller is responsible for delivering the desired performance within the specified risk range. A control mode selector specifies an appropriate situation-specific enhanced mode, which the engine controller then implements. The enhanced control modes described in this paper provide additional engine thrust or response capabilities through the modification of gains, limits, and the control algorithm, but increase the risk of engine failure. The modifications made to the engine controller to enable the use of the enhanced control modes are described, as are the interaction between the various subsystems and importantly, the interaction between the flight controller/pilot and the propulsion control system. Simulation results demonstrate how the system responds to requests for enhanced operation and the corresponding increase in performance.

Csank, Jeffrey T.↗
NASA NTRS2019

Adaptive Control Law for PID

This paper is the final report for my Spring 2019 internship at the Kennedy Space Center in Cape Canaveral, Florida. The official title of my internship is 'Launch Vehicle Control Study internship,' and I spent the spring working in GMRO- Granular Mechanics and Regolith Operations. There are two components to my project involving developing an adaptive control law for a PID controller. The first component involves performing a deep study and analysis of adaptive control laws, with the goal of developing stability proofs about the control law and the gain and phase margins. The second component involves analyzing the data received after implementing the adaptive control law. Unfortunately, as of the time of writing this paper, the data is not considered ‘clean' enough to analyze. Therefore, in this paper I will give an overview of adaptive control law stability proofs and will write about the data analysis separately. Section II includes several general definitions, and the later sections have additional definitions at the end of each section.A PID (proportional integral derivative) controller is a common control algorithm which isimplemented in NASA’s rocket launch system. The idea behind the PID controller is to calculatethe error (current position – desired position) and drive it to zero by using proportional, integral,and derivative influences on the controller. For example, when a sailor steers a ship which isheading towards location 𝑥 but would like to turn the ship to reach location 𝑥∗, he/she wouldinitially turn the wheel significantly, and as the ship proceeds towards 𝑥∗ the sailor would slowlyshift the wheel back to its original position, and thereby drive the error, 𝑥∗ − 𝑥, to zero.

Eisenberg, Yael↗
NASA NTRS1989

Analysis of modified SMI method for adaptive array weight control

An adaptive array is applied to the problem of receiving a desired signal in the presence of weak interference signals which need to be suppressed. A modification, suggested by Gupta, of the sample matrix inversion (SMI) algorithm controls the array weights. In the modified SMI algorithm, interference suppression is increased by subtracting a fraction F of the noise power from the diagonal elements of the estimated covariance matrix. Given the true covariance matrix and the desired signal direction, the modified algorithm is shown to maximize a well-defined, intuitive output power ratio criterion. Expressions are derived for the expected value and variance of the array weights and output powers as a function of the fraction F and the number of snapshots used in the covariance matrix estimate. These expressions are compared with computer simulation and good agreement is found. A trade-off is found to exist between the desired level of interference suppression and the number of snapshots required in order to achieve that level with some certainty. The removal of noise eigenvectors from the covariance matrix inverse is also discussed with respect to this application. Finally, the type and severity of errors which occur in the covariance matrix estimate are characterized through simulation.

Dilsavor, R. L.↗
DOE OSTI2024

Hot, cold, or just right? An infrared biometric sensor to improve occupant comfort and reduce overcooling in buildings via closed-loop control

To improve occupant comfort and save energy in buildings, we have developed a closed-loop air conditioning (AC) sensor-controller that predicts occupant thermal sensation from the thermographic measurement of skin temperature distribution, then uses this information to reduce overcooling (cooling-energy overuse that discomforts occupants) by regulating AC output. Taking measures to protect privacy, it combines thermal-infrared (TIR) and color (visible spectrum) cameras with machine vision to measure the skin-surface temperature profile. Since the human thermoregulation system uses skin blood flow to maintain thermoneutrality, the distribution of skin temperature can be used to predict warm, neutral, and cool thermal states. We conducted a series of human-subject thermal-sensation trials in cold-to-hot environments, measuring skin temperatures and recording thermal sensation votes. We then trained random-forest classification machine-learning models (classifiers) to estimate thermal sensation from skin temperatures or skin-temperature differences. The estimated thermal sensation was input to a proportional integral (PI) control algorithm for the AC, targeting a sensation level between neutral and warm. Our sensor-controller includes a sensor assembly, server software, and client software. The server software orients the cameras and transmits images to the client software, which in turn assesses occupant skin temperature distribution, estimates occupant thermal sensation, and controls AC operation. A demonstration conducted in a conference room in an office building near Houston, TX showed that our system reduced overcooling, decreasing AC load by 42% when the room was occupied while improving occupant comfort (fraction of “comfortable” votes) by 15 percentage points.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1987

Automatic systems and the low-level wind hazard

Automatic flight control systems provide means for significantly enhancing survivability in severe wind hazards. The technology required to produce the necessary control algorithms is available and has been made technically feasible by the advent of digital flight control systems and accurate, low-noise sensors, especially strap-down inertial sensors. The application of this technology and these means has not generally been enabled except for automatic landing systems, and even then the potential has not been fully exploited. To fully exploit the potential of automatic systems for enhancing safety in wind hazards requires providing incentives, creating demand, inspiring competition, education, and eliminating prejudicial disincentitives to overcome the economic penalties associated with the extensive and riskly development and certification of these systems. If these changes will come about at all, it will likely be through changes in the regulations provided by the certifying agencies.

Schaeffer, Dwight R.↗
NASA NTRS1989

Controller reduction for effective interdisciplinary design of active structures

Control problems of large aerospace structures are intrinsically interdisciplinary and require strategies which address the complete interaction between flexible structures, electromechanical actuators and sensors, and feedback control algorithms. Current research and future directions which will require an interdisciplinary team effort in dynamics, control and optimization of such structures are being surveyed. It is generally agreed that the dynamics of space structures require large scale discrete modeling, resulting in thousands of discrete unknowns. Proven control strategies, on the other hand, employ a low order controller that is based on a reduced order model of structures. Integration of such low order controllers and large scale dynamics models often leads to serious deterioration of the closed loop stability margin and even instability. To alleviate this stability deterioration while low order controllers remain effective, the following approach was investigated: (1) retain low order controllers based on reduced order models of structures as the basic control strategy; (2) introduce a compensator that will directly account for the deterioration of stability margin due to controller-structure integration; and (3) assess overall performance of the integrated control structure system by developing measures of suboptimality in the combination of (1) and (2). The benefits include: simplicity in the design of basic controllers, thus facilitating the optimization of structure control interactions; increased understanding of the roles of the compensator so as to modify the structure as well as the basic controller, if necessary, for improved performance; and adaptability to localize controllers by viewing the compensator as a systems integration filter.

Balas, Mark J.↗
NASA NTRS1992

Computer aided design of digital controller for radial active magnetic bearings

A five degree of freedom Active Magnetic Bearing (AMB) system is developed which is controlled by digital controllers. The model of the radial AMB system is linearized and the state equation is derived. Based on the state variables feedback theory, digital controllers are designed. The performance of the controllers are evaluated according to experimental results. The Computer Aided Design (CAD) method is used to design controllers for magnetic bearings. The controllers are implemented with a digital signal processing (DSP) system. The control algorithms are realized with real-time programs. It is very easy to change the controller by changing or modifying the programs. In order to identify the dynamic parameters of the controlled magnetic system, a special experiment was carried out. Also, the online Recursive Least Squares (RLS) parameter identification method is studied. It can be realized with the digital controllers. Online parameter identification is essential for the realization of an adaptive controller.

Cai, Zhong↗
NASA NTRS1993

Pump and Flow Control Subassembly of Thermal Control Subsystem for Photovoltaic Power Module

The pump and flow control subassembly (PFCS) is an orbital replacement unit (ORU) on the Space Station Freedom photovoltaic power module (PVM). The PFCS pumps liquid ammonia at a constant rate of approximately 1170 kg/hr while providing temperature control by flow regulation between the radiator and the bypass loop. Also, housed within the ORU is an accumulator to compensate for fluid volumetric changes as well as the electronics and firmware for monitoring and control of the photovoltaic thermal control system (PVTCS). Major electronic functions include signal conditioning, data interfacing and motor control. This paper will provide a description of each major component within the PFCS along with performance test data. In addition, this paper will discuss the flow control algorithm and describe how the nickel hydrogen batteries and associated power electronics will be thermally controlled through regulation of coolant flow to the radiator.

Motil, Brian↗
NASA NTRS2002

Estimator Based Controller for High Speed Flywheel Magnetic Bearing System

A flywheel system and its operator interface are described. Measurements of magnetic bearing negative stiffness are performed. Two digital magnetic bearing control algorithms (PD and estimator based) are defined and their implementations are described. Tuning of each controller is discussed. Comparison of the two controllers' stability, damping noise, and operating current are described. Results describing the superiority of the estimator-based controller are presented and discussed.

Dever, Timothy P.↗
NASA NTRS2005

Planner-Based Control of Advanced Life Support Systems

The paper describes an approach to the integration of qualitative and quantitative modeling techniques for advanced life support (ALS) systems. Developing reliable control strategies that scale up to fully integrated life support systems requires augmenting quantitative models and control algorithms with the abstractions provided by qualitative, symbolic models and their associated high-level control strategies. This will allow for effective management of the combinatorics due to the integration of a large number of ALS subsystems. By focusing control actions at different levels of detail and reactivity we can use faster: simpler responses at the lowest level and predictive but complex responses at the higher levels of abstraction. In particular, methods from model-based planning and scheduling can provide effective resource management over long time periods. We describe reference implementation of an advanced control system using the IDEA control architecture developed at NASA Ames Research Center. IDEA uses planning/scheduling as the sole reasoning method for predictive and reactive closed loop control. We describe preliminary experiments in planner-based control of ALS carried out on an integrated ALS simulation developed at NASA Johnson Space Center.

Muscettola, Nicola↗
NASA NTRS2010

Analysis of Air Traffic Track Data with the AutoBayes Synthesis System

The Next Generation Air Traffic System (NGATS) is aiming to provide substantial computer support for the air traffic controllers. Algorithms for the accurate prediction of aircraft movements are of central importance for such software systems but trajectory prediction has to work reliably in the presence of unknown parameters and uncertainties. We are using the AutoBayes program synthesis system to generate customized data analysis algorithms that process large sets of aircraft radar track data in order to estimate parameters and uncertainties. In this paper, we present, how the tasks of finding structure in track data, estimation of important parameters in climb trajectories, and the detection of continuous descent approaches can be accomplished with compact task-specific AutoBayes specifications. We present an overview of the AutoBayes architecture and describe, how its schema-based approach generates customized analysis algorithms, documented C/C++ code, and detailed mathematical derivations. Results of experiments with actual air traffic control data are discussed.

Schumann, Johann Martin Philip↗