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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Fail-fixed servovalve with positive fluid feedback

The servovalve includes a primary jet of fluid. A variable control signal is adapted to vary the angular position of the primary jet from its maximum recovery position. A first fluid path is adapted to supply fluid to a servopiston at a variable pressure determined at least in part by the control signal. A second fluid path is adapted to receive a predetermined portion of the primary jet fluid when the control signal reaches a predetermined value. The second fluid path terminates in the vicinity of the primary jet and is adapted to direct a secondary jet of fluid at the primary jet to deflect the primary jet toward the input orifice of the second fluid path. The resultant positive fluid feedback in the second fluid path causes the primary jet to latch in a first angular position relative to the maximum recovery position when the control signal reaches a predetermined value. The servovalve may further include a means to discharge the fluid and a means to block the first fluid path to the servopiston when the control signal falls below a second predetermined value. A method of operating a fail-fixed servovalve is also described.

Kast, Howard B.↗
DOE OSTI2022

Real-Sim Interface: Enabling Multi-resolution Simulation and X-in-the-Loop Development for Connected and Automated Vehicles

We report connected and automated vehicles (CAVs) can bring safety, mobility, and energy benefits to transportation systems. Ideally, CAV applications would be fully evaluated and validated prior to real-world implementation. However, many technical challenges in both software and hardware hinder the process. To comprehensively evaluate all aspects of CAV applications, an integrated evaluation environment is needed with various simulation tools from different domains. In the current literature, there lacks a well-developed interface to enable multi-resolution simulation of vehicle, traffic, virtual environment, and hardware-in-the-loop (HIL) simulation. In this work, a modular and flexible interface is developed to enable multi-resolution vehicle and traffic co-simulation for CAV applications. This interface is built upon Oak Ridge National Laboratory’s (ORNL’s) Real-Sim approach, can support various simulation tools and real-time X-in-the-loop (XIL) simulations, and is based on network communication protocols. The network communication delays are analyzed for simultaneous connection of up to 20 simulators. Then, two example applications are studied to demonstrate the potential usage of the Real-Sim interface: (1) a centralized merging scenario where the dynamics of two ego vehicles are emulated with detailed vehicle and powertrain dynamics models and (2) a signal-controller-in-the-loop (SCIL) evaluation where one intersection of the simulated traffic scenario is controlled by a physical signal controller. This Real-Sim interface is a tool that allows researchers to bring real, tangible hardware and software into simulated environments to comprehensively evaluate and support a wide variety of CAV applications.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1988

Nanosequencer digital logic controller

A digital logic controller provides instruction execution times on the order of 50 nanoseconds and employing read-only memory outputting instructions to a pipeline register, a portion of each instruction providing a status-select control signal and address signals for controlling selection of the next instruction from the read-only memory.

Charles R Lahmeyer↗
NASA NTRS1990

Robust, High-Performance Control For Robotic Manipulators

Improved control scheme for robotic manipulators results from alternative approach to use of both model-based and performance-based control techniques. Includes feedforward controller and separate feedback controller. Feedforward controller model-based and contains any known part of dynamics of manipulator used to produce nominal control signal. Feedback controller performance-based; compensates for any unknown dynamics and uncertainties or variations in parameters of manipulator and/or payload.

Seraji, Homayoun↗
DOE OSTI2020

Real-time simulator and controller of power system using distributed data streaming server

Systems and methods for simulating and controlling a power system in real time, using a controller, are provided. The controller includes a simulation layer to simulate an operation of the power system, a disturbance generation layer to provide data to the simulation layer to disturb the simulated operation of the power system, an application layer to display the simulated operation of the power system and generate a control signal to control, based on the simulated operation of the power system, at least one element of the power system, and a distributed data streaming server (D2S2) to allow interoperability among the simulation layer, the disturbance layer, and the application layer.

Li, Fangxing↗
DOE OSTI2023

Development of A Hardware-In-the-Loop (HIL) Testbed for Cyber-Physical Security in Smart Buildings

As smart buildings move towards open communication technologies, providing access to the Building Automation System (BAS) through the building's intranet, or even remotely through the Internet, has become a common practice. However, BAS was historically developed as a closed environment and designed with limited cyber-security considerations. Thus, smart buildings are vulnerable to cyber-attacks with the increased accessibility. This study introduces the development and capability of a Hardware-in-the-Loop (HIT) testbed for testing and evaluating the cyber-physical security of typical BASs in smart buildings. The testbed consists of three subsystems: (1) a real-time HIL emulator simulating the behavior of a virtual building as well as the Heating, Ventilation, and Air Conditioning (HVAC) equipment via a dynamic simulation in Modelica; (2) a set of real HVAC controllers monitoring the virtual building operation and providing local control signals to control HVAC equipment in the HIL emulator; and (3) a BAS server along with a web-based service for users to fully access the schedule, setpoints, trends, alarms, and other control functions of the HVAC controllers remotely through the BACnet network. The server generates rule-based setpoints to local HVAC controllers. Based on these three subsystems, the HIL testbed supports attack/fault-free and attack/fault-injection experiments at various levels of the building system. The resulting test data can be used to inform the building community and support the cyber-physical security technology transfer to the building industry.

Li, Guowen↗
NASA NTRS1988

The efficacy of using human myoelectric signals to control the limbs of robots in space

This project was designed to investigate the usefulness of the myoelectric signal as a control in robotics applications. More specifically, the neural patterns associated with human arm and hand actions were studied to determine the efficacy of using these myoelectric signals to control the manipulator arm of a robot. The advantage of this approach to robotic control was the use of well-defined and well-practiced neural patterns already available to the system, as opposed to requiring the human operator to learn new tasks and establish new neural patterns in learning to control a joystick or mechanical coupling device.

Clark, Jane E.↗
DOE OSTI2022

Network-Level Traffic Signal Cooperation: A Higher-Order Conflict Graph Approach

Traffic signal control and cooperation are extremely important to alleviate traffic congestion in a large traffic network. This study develops a higher-order conflict graph approach for network-wide traffic signal control and cooperation. A conflict graph is applied to model the traffic signal configurations, which identifies the conflict and unconflicted movements for each intersection. In conflict graph, the node represents each movement. The weight of each node can be defined as traffic volume, queue length, fuel consumption, or any weighted combinations of these measurements. The calculation of the optimal green light duration and green light sequence (for different movements) is equivalent to sequentially finding the maximum weight independent set (MWIS) in the conflict graph. The conflict graph also provides a uniform and efficient way to connect traffic signal operations among nearby intersections spatially. Then, we introduced the concept of the k -th order neighborhood to model the degree of connectivity between each movement to the movements at upstream or downstream intersections. The weight of each node in the higher-order conflict graph not only represents its own congestion level, but also relates to the traffic conditions of nearby intersections. Through this approach, the cooperation of multiple intersections can be realized by incorporating their spatial connectivity into conflict graph and solving the MWIS problem. A simulation network is built in SUMO to test the effectiveness of the proposed method. Results suggested that the proposed model outperformed other state-of-the-art signal control methods. Also, the scheme maintains good performance under varying traffic demands.

42 ENGINEERING↗
NASA NTRS1973

The application of standardized control and interface circuits to three dc to dc power converters.

Standardized control and interface circuits were applied to the three most commonly used dc to dc converters: the buck-boost converter, the series-switching buck regulator, and the pulse-modulated parallel inverter. The two-loop ASDTIC regulation control concept was implemented by using a common analog control signal processor and a novel digital control signal processor. This resulted in control circuit standardization and superior static and dynamic performance of the three dc-to-dc converters. Power components stress control, through active peak current limiting and recovery of switching losses, was applied to enhance reliability and converter efficiency.

Yu, Y.↗
NASA NTRS2011

Input and Output Performance of M-MRAC in the Presence of Bounded Disturbances

This paper presents performance analysis of novel modified model reference adaptive control (M-MRAC) architecture in conjunction with different robust adaptive laws for the uncertain linear systems subject to unknown but bounded disturbances. It is shown that for any robust adaptive law the tracking error of the M-MRAC system can be arbitrarily decreased in transient and in the steady-state by increasing the adaptation rate, without generating high frequency oscillations in the control signal, which are unavoidable in conventional MRAC systems for large adaptation rates. Moreover, the generated adaptive control signal arbitrary closely tracks the ideal control signal when the error feedback gain is simultaneously increased with the adaptation rate, according to derived rule. The results are demonstrated via simulations.

Stepanyan, Vahram↗
NASA NTRS2008

Systems and methods for self-synchronized digital sampling

Systems and methods for self-synchronized data sampling are provided. In one embodiment, a system for capturing synchronous data samples is provided. The system includes an analog to digital converter adapted to capture signals from one or more sensors and convert the signals into a stream of digital data samples at a sampling frequency determined by a sampling control signal; and a synchronizer coupled to the analog to digital converter and adapted to receive a rotational frequency signal from a rotating machine, wherein the synchronizer is further adapted to generate the sampling control signal, and wherein the sampling control signal is based on the rotational frequency signal.

Samson, Jr., John R.↗
NASA NTRS1983

Adaptive reference voltage generator for firing angle control of line-commutated inverters

A control system for a permanent-magnet motor driven by a multiphase line-commulated inverter is described. It is provided with integrators for integrating the back EMF of each phase of the motor for use in generating system control signals for an inverter gate logic using a sync and firing angle control generator connected to the outputs of the integrators. The firing angle control signals are produced by the control generator by means for combining 120 deg segments of the integrated back EMF signals symmetrical about their maxima into composite positive and negative waveforms, and means for sampling the maxima of each waveform every 120 deg. These samples are then used as positive and negative firing angle control signals. Whereby any change in amplitude of the integrated back EMF signals will not affect a change in the operating power factor of the motor and inverter.

Dolland, C. R.↗
NASA NTRS1987

Method and apparatus for telemetry adaptive bandwidth compression

Methods and apparatus are provided for automatic and/or manual adaptive bandwidth compression of telemetry. An adaptive sampler samples a video signal from a scanning sensor and generates a sequence of sampled fields. Each field and range rate information from the sensor are hence sequentially transmitted to and stored in a multiple and adaptive field storage means. The field storage means then, in response to an automatic or manual control signal, transfers the stored sampled field signals to a video monitor in a form for sequential or simultaneous display of a desired number of stored signal fields. The sampling ratio of the adaptive sample, the relative proportion of available communication bandwidth allocated respectively to transmitted data and video information, and the number of fields simultaneously displayed are manually or automatically selectively adjustable in functional relationship to each other and detected range rate. In one embodiment, when relatively little or no scene motion is detected, the control signal maximizes sampling ratio and causes simultaneous display of all stored fields, thus maximizing resolution and bandwidth available for data transmission. When increased scene motion is detected, the control signal is adjusted accordingly to cause display of fewer fields. If greater resolution is desired, the control signal is adjusted to increase the sampling ratio.

Graham, Olin L.↗
NASA NTRS2014

Applying Workspace Limitations in a Velocity-Controlled Robotic Mechanism

A robotic system includes a robotic mechanism responsive to velocity control signals, and a permissible workspace defined by a convex-polygon boundary. A host machine determines a position of a reference point on the mechanism with respect to the boundary, and includes an algorithm for enforcing the boundary by automatically shaping the velocity control signals as a function of the position, thereby providing smooth and unperturbed operation of the mechanism along the edges and corners of the boundary. The algorithm is suited for application with higher speeds and/or external forces. A host machine includes an algorithm for enforcing the boundary by shaping the velocity control signals as a function of the reference point position, and a hardware module for executing the algorithm. A method for enforcing the convex-polygon boundary is also provided that shapes a velocity control signal via a host machine as a function of the reference point position.

Abdallah, Muhammad E.↗
DOE OSTI2022

Machine Learning-based Cyber-Physical Anomaly Detection in Wide Area Voltage Control Systems

Wide-area voltage control systems (WAVCS) are widely deployed in power grid to improve the voltage stability in transmission system using Flexible AC Transmission System (FACTS) devices. The WAVCS relies on wide-area measurement and control signals for closed-loop control of FACTS devices to improve the transient voltage stability in power grid in real-time. Since the WAVCS utilizes a cyber-layer communication during its normal operation, they are susceptible to cyber attacks from adversaries which can lead to a voltage collapse if the attacks go undetected and unmitigated. This paper proposes a supervised machine learning (ML)-based anomaly detection algorithm for detecting various stealthy cyber attacks in the context of WAVCS cybersecurity. In particular, a fuzzy logic-based wide-area controller, as proposed by the Bonneville Power Administration (BPA), is implemented on the Kundur’s four machine two-area system that is integrated with a static var compensator (SVC) to improve voltage profile on sensitive buses. Later, different types of data integrity attacks, including pulse and ramp attacks, are considered on the wide-area measurement and control signals to analyze the performance of the proposed anomaly detector. Our experimental evaluation shows a promising performance with a high true-positive rate (more than 99%) and low false-negative rate (less than 1%) while exhibiting a small prediction time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Traffic Signal Optimization by Integrating Reinforcement Learning and Digital Twins

Machine learning (ML) methods, especially reinforcement learning (RL), have been widely considered for traffic signal optimization in intelligent transportation systems. Most of these ML methods are centralized, lacking in scalability and adaptability in large traffic networks. Further, it is challenging to train such ML models due to the lack of training platforms and/or the cost of deploying and training in a real traffic networks. This paper presents an approach for the integration of decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin (DT) to optimize traffic signals for the reduction of traffic congestion and network-wide fuel consumption related to stopping. Specifically, the DGMARL agents learn traffic state patterns and make decisions regarding traffic signal control with assistance from a Digital Twin module, which simulates and replicates the traffic behaviors of a real traffic network. The proposed approach was evaluated using PTV-Vissim [1], a microscopic traffic simulation platform. PTV-Vissim is also the simulation engine of the DT, enabling emulation and optimization of the traffic signals on the MLK Smart Corridor in Chattanooga, Tennessee. Compared to an actuated signal control baseline approach, experiment results show that Eco_PI, a developed performance measure capturing the impact of stops on fuel consumption, was reduced by 44.27% in a 24-hour and an average of 29.88% in a PM-peak-hour scenario.

Multi-Agent Reinforcement Learning, Digital Twin, ↗
DOE OSTI2024

Simulation Evaluation of a Large-Scale Implementation of Virtual-Phase Link-Based Model Predictive Control

Traffic congestion is a serious problem in the US, and traffic signal control is one of the effective solutions to congestion. Previous research on model predictive control (MPC)-based traffic signal control showed substantial benefits over conventional methods. This study focused on implementing MPC over a large-scale network with complex intersections and the impact of cycle length, network size, and imperfect state estimation on performances. This study implemented a virtual phase link (VPL)-based model predictive control method which used the number of vehicles in each VPL as input state variables and was suitable for National Electrical Manufacturing Association (NEMA) ring-barrier control. To test the impact of network size, the performance of distributed MPC (36 intersections in the network are divided into five subnetworks) was compared with that of MPC over the full network for a set of cycle lengths. To test the impact of imperfect state estimation, we synthetically infused estimation error and developed two scenarios, MPC-error and MPC-error narrow, which had higher and lower estimation errors, respectively. The performance of these MPC methods was compared with that of the existing time-of-day (TOD) method and an offline method that used Webster's method for split and MULTIBAND for cycle length and offset optimization. Trajectory and linkwise signal performance measures were collected from the simulation to evaluate performance. The distributed MPC method with perfect state estimation had the lowest delay and highest energy efficiency of all the methods. The performance of MPC decreased as the prediction inaccuracy increased. MPC-error had 7% and 11% more delay than MPC-error narrow in the morning and evening peaks, respectively. Overall, simulation results suggest that even with imperfect state estimation, MPC methods will outperform offline methods significantly.

large-scale simulation↗