Physics-Informed Spatiotemporal Deep Learning for Emulating Coupled Dynamical Systems
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Control and Scaling Approach for the Emulation of Dynamic Subscale Torque Loads
Research and development of electrified aircraft propulsion powertrains is moving toward the use electro-mechanical systems to emulate the loads a system imparts on another. Replacing a prime mover with a model driving an electro-mechanical system capable of emulating loads that regulate the system to produce a desired response is a lower risk, lower cost alternative to using the traditional prime mover for control system verification. This paper outlines a control and scaling approach for emulating scaled dynamic torque loads using electric machine (EM) hardware for electrified aircraft propulsion research and development purposes. The approach, known as the Sliding Mode Impedance Controller with Scaling (SMICS), drives a mechanically coupled two-EM system that provides a scaled hardware representation of an electrified turbomachinery shaft. One EM reflects inertial dynamics and load of the shaft under steady-state and transient operation while the second EM represents a motor/generator connected to the shaft. This closed loop system applies impedance and sliding mode control schemes to match desired dynamics in real-time along with parameter scaling to effectively scale full scale torque inputs, a full-scale desired inertia, and sub-scale speed feedback. The result is a sub-scale hardware implementation of a coupled EM system that is command-able by a model and control system designed for a full-scale electrified aircraft propulsion powertrain. The paper elaborates on the need for closed loop control and scaling as well as impedance and sliding mode control theory, shows a derivation of the controller and scaling, its implementation, and presents a comparison of theoretical and actual simulation results acquired during hardware-in-the-loop testing of a partial turboelectric propulsion concept at the NASA Electric Aircraft Testbed (NEAT).
Santino J Bianco↗
Propulsion Electric Grid Simulator (PEGS) for Future Turboelectric Distributed Propulsion Aircraft
NASA Glenn Research Center, in collaboration with the aerospace industry and academia, has begun the development of technology for a future hybrid-wing body electric airplane with a turboelectric distributed propulsion (TeDP) system. It is essential to design a subscale system to emulate the TeDP power grid, which would enable rapid analysis and demonstration of the proof-of-concept of the TeDP electrical system. This paper describes how small electrical machines with their controllers can emulate all the components in a TeDP power train. The whole system model in Matlab/Simulink was first developed and tested in simulation, and the simulation results showed that system dynamic characteristics could be implemented by using the closed-loop control of the electric motor drive systems. Then we designed a subscale experimental system to emulate the entire power system from the turbine engine to the propulsive fans. Firstly, we built a system to emulate a gas turbine engine driving a generator, consisting of two permanent magnet (PM) motors with brushless motor drives, coupled by a shaft. We programmed the first motor and its drive to mimic the speed-torque characteristic of the gas turbine engine, while the second motor and drive act as a generator and produce a torque load on the first motor. Secondly, we built another system of two PM motors and drives to emulate a motor driving a propulsive fan. We programmed the first motor and drive to emulate a wound-rotor synchronous motor. The propulsive fan was emulated by implementing fan maps and flight conditions into the fourth motor and drive, which produce a torque load on the driving motor. The stator of each PM motor is designed to travel axially to change the coupling between rotor and stator. This feature allows the PM motor to more closely emulate a wound-rotor synchronous machine. These techniques can convert the plain motor system into a unique TeDP power grid emulator that enables real-time simulation performance using hardware-in-the-loop (HIL).
electric power grid emulator↗
Development of a water source heat pump hardware-in-the-loop (HIL) testing facility for smart building applications
Over the last decade, the global fight against climate change through electrification has led to an increase in research on building heating, ventilation, and air conditioning (HVAC) systems that utilize intelligent control algorithms to provide demand-side grid service while maintaining the thermal comfort of building occupants. As the pivotalpoint between building electricity consumption and indoor thermal comfort, high-efficiency electrical heatpumps are at the center of these emerging studies, and various grid-interactive and occupant-comfort control algorithms have been developed for them. The impact of these algorithms on the heatpump operation andperformance under different weather, building load, and grid requests calls for investigation and verification via experimental tests with actual heat pumps integrated with real-time building and grid responses. This study presents a Water-Source Heat Pump Hardware-in-The-Loop (HIL) Test Facility developed with the capability to perform such tests. The hardware configuration for this testfacility introduces a hydronic system that emulates the conditions for the heat pump water-side, and a duct system that emulates conditions for the heat pump airside. Both data acquisition and emulator control are implemented through the National Instruments (NI) LabVIEW software running on an NI PXIplatform. The HIL mechanism based on the hardware-software integration that allows the testbed to communicate with a generic simulation environment is also discussed. Currently, the test facility setup includes a single heatpump and virtual building model in EnergyPlus coupled with an occupant behavioral model in MATLAB. Preliminary test results of the current setup demonstrate the building load emulator's ability to track the simulated gone temperature with a Root Mean Square Deviation (RSME) below 0.12°C (0.216°F). An uncertainty analysis based on sensor accuracies shows that the heat pump coefficient of performance (COP) can be measured with a relative uncertainty of 10.4% in cooling and 3.7% in heating. Apartfrom the current testing on a single heat pump, the test facility also provides the flexibility to include additional heat pumps to form a heat pump cluster, as well as coupling the heat pump with active thermal storage to provide enhanced demandflexibility.
Calfa, Caleb↗
Performance of A Real-Time Photon Counting Optical Receiver in the Presence of Emulated Channel Fading
Free-space optical communication links with terrestrial ground stations experience fading due to atmospheric scintillation and beam pointing. Fiber-coupled receiver systems experience additional fading at the interface between the fiber and free-space optics of the telescope. The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) has characterized a real-time photon-counting optical ground receiver system with an atmospheric fade emulation system. The receiver system is comprised of a fiber interconnect, an array of superconducting nanowire single photon detectors (SNSPDs), and a field programmable gate array (FPGA) based receive modem. Two fiber interconnect/detector architectures have been studied. One architecture uses a 70-mode photonic lantern coupled to seven single pixel SNSPDs. The other architecture uses a 10-mode few-mode fiber (FMF) coupled to a 15-pixel SNSPD array. The receiver system complies with the Consultative Committee for Space Data Systems (CCSDS) Optical Communications High Photon Efficiency Coding and Synchronization Standard, which uses serially concatenated convolutionally coded pulse-position modulation (SCPPM). The CCSDS standard is designed for use in low photon flux missions, including the Orion Artemis-II Optical (O2O) communications demonstration. The standard utilizes a convolutional symbol interleaver which can be resized to mitigate different fades. The fade emulation system employed in this work emulates scintillation-induced, pointing-induced, and coupling-induced fading. This paper gives an overview of the real-time optical receiver system and the fade emulation system. It presents tests results which show the impact of fading on the performance on the receiver. The test results show that in the presence of channel fading, the 70-mode photonic lantern outperforms the 10-mode FMF under higher (D/r_0=9) turbulence conditions due to high fiber-coupling-induced fading and fiber coupling loss on the 10-mode FMF. When operating in lower turbulence (D/r_0=4), the 10-mode FMF outperforms the 70-mode photonic lantern. The paper also shows a larger convolutional interleaver improves the system performance as long as the receiver does not lose acquisition.
optical communications↗
Performance of a real-time photon counting optical receiver in the presence of emulated channel fading
Free-space optical communication links with terrestrial ground stations experience fading due to atmospheric scintillation and beam pointing. Fiber-coupled receiver systems experience additional fading at the interface between the fiber and free-space optics of the telescope. The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) has characterized a real-time photon-counting optical ground receiver system with an atmospheric fade emulation system. The receiver system is comprised of a fiber interconnect, an array of superconducting nanowire single photon detectors (SNSPDs), and a field programmable gate array (FPGA) based receive modem. Two fiber interconnect/detector architectures have been studied. One architecture uses a 70-mode photonic lantern coupled to seven single pixel SNSPDs. The other architecture uses a 10-mode few-mode fiber (FMF) coupled to a 15-pixel SNSPD array. The receiver system complies with the Consultative Committee for Space Data Systems (CCSDS) Optical Communications High Photon Efficiency Coding and Synchronization Standard, which uses serially concatenated convolutionally coded pulse-position modulation (SCPPM). The CCSDS standard is designed for use in low photon flux missions, including the Orion Artemis-II Optical (O2O) communications demonstration. The standard utilizes a convolutional symbol interleaver which can be resized to mitigate different fades. The fade emulation system employed in this work emulates scintillation-induced, pointing-induced, and coupling-induced fading. This paper gives an overview of the real-time optical receiver system and the fade emulation system. It presents tests results which show the impact of fading on the performance on the receiver. The test results show that in the presence of channel fading, the 70-mode photonic lantern outperforms the 10-mode FMF under higher (D/r_0=9) turbulence conditions due to high fiber-coupling-induced fading and fiber coupling loss on the 10-mode FMF. When operating in lower turbulence (D/r_0=4), the 10-mode FMF outperforms the 70-mode photonic lantern. The paper also shows a larger convolutional interleaver improves the system performance as long as the receiver does not lose acquisition.
optical communications↗
Emulation and detection of physical faults and cyber-attacks on building energy systems through real-time hardware-in-the-loop experiments
The increasing use of remote or mobile access, integrated wearable technologies, data exchange, and cloud-based data analytics in modern smart buildings is steering the building industry towards open communication technologies. The increased connectivity and accessibility could lead to more cyber-attacks in smart buildings. On the other hand, physical faults (e.g., HVAC -heating, ventilation, and air-conditioning faults) may have similar adverse impacts as those from the cyber-attacks on building energy systems, such as occupant discomfort, energy wastage, and equipment downtime. However, current physical behavior-based anomaly detection methods fail to differentiate between cyber-attacks and physical faults in building energy systems. Moreover, the challenge in collecting real-world threat data with ground truth has led researchers to rely on numerical models with user-defined assumptions, which may not accurately reflect real-world conditions due to the lack of in-situ experimental datasets. To address these challenges and gaps, this paper presents a flexible hardware-in-the-loop (HIL) testbed for generating cyber-attack and physical fault datasets and demonstrating threat detection algorithms in a real building automation system (BAS) environment. This testbed combines hardware (i.e., real BAS with local HVAC controllers and a physical network) with software (i.e., high-fidelity models to represent behaviors of building envelope and HVAC energy systems), enabling emulations of realistic threats. Five HIL experiments, including one baseline without any threats, two with physical faults, and two with cyber-attacks, were conducted to generate datasets containing detailed network traffic and system states. A joint classification framework, incorporating a network analyzer and a physical HVAC fault detector, was proposed to automatically detect cyber-physical abnormalities on BAS at both the network and the physical HVAC levels. The network analyzer comprises a conditional random fields (CRF) based command validator and a statistics-based detection strategy. The fault detector employs a weather and schedule-based pattern matching and feature-based principal component analysis (WPM-FPCA) method. Evaluation of the classification using four metrics from the multi-class confusion matrix revealed an average accuracy of 90.2%, recall of 89.7%, precision of 88.5% and F1-score of 89.2%. Finally, these results demonstrate that the proposed joint classification framework can effectively differentiate between specific types of cyber-attacks (e.g., device reinitialization attack, network Denial-of-Service attack) and physical faults (e.g., air handling unit operational fault, cooling coil valve stuck) in real time for improved building energy management.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Propulsion Powertrain Real-Time Simulation Using Hardware-in-the-Loop (HIL) for Aircraft Electric Propulsion System
It is essential to design a propulsion powertrain real-time simulator using the hardware-in-the-loop (HIL) system that emulates an electrified aircraft propulsion (EAP) systems power grid. This simulator would enable us to facilitate in-depth understanding of the system principles, to validate system model analysis and performance prediction, and to demonstrate the proof-of-concept of the EAP electrical system. This paper describes how subscale electrical machines with their controllers can mimic the power components in an EAP powertrain. In particular, three powertrain emulations are presented to mimic 1) a gas turbo-=shaft engine driving a generator, consisting of two permanent magnet (PM) motors with brushless motor drives, coupled by a shaft, 2) a motor driving a propulsive fan, and 3) a turbo-shaft engine driven fan (turbofan engine) operation. As a first step towards the demonstration, experimental dynamic characterization of the two motor drive systems, coupled by a mechanical shaft, were performed. The previously developed analytical motor models1 were then replaced with the experimental motor models to perform the real-time demonstration in the predefined flight path profiles. This technique can convert the plain motor system into a unique EAP power grid emulator that enables rapid analysis and real-time simulation performance using hardware-in-the-loop (HIL).
turbo-electric propulsion↗
NREL’s Cyber-Energy Emulation Platform for Research and System Visualization
This paper presents NREL’s Cyber Energy Emulation (CEE) Platform. This is a novel emulation platform for achieving real-time visualization of large-scale environments involving cyber-physical devices. It allows for the environment to include real, physical hardware, along with emulated devices communicating with each other as part of the same system. The CEE Platform is also capable of streaming, collecting, storing, transporting, and visualizing all data within the emulated environment. By providing this capability, it enables high-fidelity visual analysis of events to be performed in real time as well as the use of historical data for forensic analysis. This paper presents the design of the CEE Platform as well as several potential use cases and applications. It also aims to highlight why this type of visualization tool has potential for research and education about cyber-physical systems.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Development of the CELSS Emulator at NASA JSC
The Controlled Ecological Life Support System (CELSS) Emulator is under development at the NASA Johnson Space Center (JSC) with the purpose to investigate computer simulations of integrated CELSS operations involving humans, plants, and process machinery. This paper describes Version 1.0 of the CELSS Emulator that was initiated in 1988 on the JSC Multi Purpose Applications Console Test Bed as the simulation framework. The run module of the simulation system now contains a CELSS model called BLSS. The CELSS Emulator makes it possible to generate model data sets, store libraries of results for further analysis, and also display plots of model variables as a function of time. The progress of the project is presented with sample test runs and simulation display pages.
Cullingford, Hatice S.↗
Control and Scaling Approach for the Emulation of Dynamic Subscale Torque Loads
Research and development of electrified aircraft propulsion powertrains are relying on the use of electromechanical systems to emulate turbomachinery/rotor loads. Replacing a physical turbomachinery/rotor with a model driving a subscale electromechanical system capable of emulating subscale torque loads and responses is a lower risk, lower cost alternative to using the full-scale turbomachinery/rotor for initial control system verification. This paper outlines a novel control and scaling approach for emulating dynamic subscale torque loads using electric machine (EM) hardware for electrified aircraft propulsion research and development purposes. The approach, known as the Sliding Mode Impedance Controller with Scaling (SMICS), drives a mechanically coupled, two-EM system to behave like a subscale hardware representation of a hybrid-electric turbomachinery shaft. One EM reflects the inertial dynamics and torque load of the subscale turbomachinery under steady-state and transient operation while the second EM represents a motor/generator connected to the shaft, which is intended to hybridize the turbomachinery. This closed loop control and scaling algorithm applies impedance and sliding mode control schemes, along with parameter scaling, to match subscale, desired dynamics in real-time and to allow this system to be driven by a full-scale hybrid-electric turbomachinery model and control. The paper elaborates on the concept of the closed loop control and scaling approach and explains the significance of using impedance and sliding mode control. It shows a derivation of the closed loop control and scaling algorithm, its implementation, and presents a comparison of theoretical and actual simulation results acquired during hardware-in-the-loop testing of a partial turboelectric propulsion concept aircraft at the NASA Electric Aircraft Testbed (NEAT).The results show that the intended dynamic responses of the hardware and the aircraft model are achieved in both the time and frequency domain. Full scale propulsion control systems can be tested using this hardware and software approach.
Emulation↗
Neural networks for self-learning control systems
It is shown how a neural network can learn of its own accord to control a nonlinear dynamic system. An emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. The controller, another multilayered neural network, next learns to control the emulator. The self-trained controller is then used to control the actual dynamic system. The learning process continues as the emulator and controller improve and track the physical process. An example is given to illustrate these ideas. The 'truck backer-upper,' a neural network controller that steers a trailer truck while the truck is backing up to a loading dock, is demonstrated. The controller is able to guide the truck to the dock from almost any initial position. The technique explored should be applicable to a wide variety of nonlinear control problems.
Nguyen, Derrick H.↗
Emulation of Core Flight System Applications for Flight Software Development and Validation
The Mars Sample Return (MSR) campaign is an unprecedented attempt in the return of Martian samples back to Earth. The ascent from the surface will be performed by the Mars Ascent Vehicle (MAV), a critical element in the mission that National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC) is developing. To this end, innovations in flight software development, verification, and validation are occurring. The MAV flight computer will run Core Flight System (cFS), an open-source software environment developed by NASA Goddard Space Flight Center (GSFC). NASA Marshall’s MAV Mission and Fault Management (M&FM) Team has implemented an emulation of two applications of this architecture: Limit Checker and Stored Command. Using an emulation of the functionalities of these applications allows for rapid prototyping of table-based algorithms. Further, M&FM is leveraging an in-house, low-fidelity but high-throughput State Analysis Model (SAM), an integrated MATLAB Stateflow Plant and Software model. This model is run in parallel with the cFS emulation for full flyout testing of the M&FM algorithms, verification of intent of these algorithms, and for future auto-generation of application-ingestible M&FM tables. The tables can then be delivered to the MAV Flight Software (FSW) team in a seamless process, reducing the cost of traditional FSW development and the risk of starting M&FM FSW development at later points in the NASA program life cycle.
Cody Wheeler↗
Emulation of Core Flight System Applications for Flight Software Development and Validation
The Mars Sample Return (MSR) campaign is an unprecedented attempt in the return of Martian samples back to Earth. The ascent from the surface will be performed by the Mars Ascent Vehicle (MAV), a critical element in the mission that National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC) is developing. To this end, innovations in flight software development, verification, and validation are occurring. The MAV flight computer will run Core Flight System (cFS), an open-source software environment developed by NASA Goddard Space Flight Center (GSFC). NASA Marshall’s MAV Mission and Fault Management (M&FM) Team has implemented an emulation of two applications of this architecture: Limit Checker and Stored Command. Using an emulation of the functionalities of these applications allows for rapid prototyping of table-based algorithms. Further, M&FM is leveraging an in-house, low-fidelity but high-throughput State Analysis Model (SAM), an integrated MATLAB Stateflow Plant and Software model. This model is run in parallel with the cFS emulation for full flyout testing of the M&FM algorithms, verification of intent of these algorithms, and for future auto-generation of application-ingestible M&FM tables. The tables can then be delivered to the MAV Flight Software (FSW) team in a seamless process, reducing the cost of traditional FSW development and the risk of starting M&FM FSW development at later points in the NASA program life cycle.
Cody Wheeler↗
Development of the CELSS emulator at NASA. Johnson Space Center
The Closed Ecological Life Support System (CELSS) Emulator is under development. It will be used to investigate computer simulations of integrated CELSS operations involving humans, plants, and process machinery. Described here is Version 1.0 of the CELSS Emulator that was initiated in 1988 on the Johnson Space Center (JSC) Multi Purpose Applications Console Test Bed as the simulation framework. The run model of the simulation system now contains a CELSS model called BLSS. The CELSS simulator empowers us to generate model data sets, store libraries of results for further analysis, and also display plots of model variables as a function of time. The progress of the project is presented with sample test runs and simulation display pages.
Cullingford, Hatice S.↗
OT Emulation Data Broker
The OT Emulation Data Broker system allows Simulink models to be connected to an emulated control system network. The package includes a Simulink S-Function that allows communication to the data broker via inter process communication; a data broker, which orchestrates communication between the emulated control system network and the simulation; an endpoint, which facilitates communication between the data broker and PLC's on the control network using ModBus/TCP; and an example PLC structured text files that work with OpenPLC, an open source emulated PLC. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-11479 O
Hahn, Andrew↗
OT Emulation Data Broker v.2.0
SAND2021-11479 O The OT Emulation Data Broker system allows Simulink models to be connected to an emulated control system network. The package includes a Simulink S-Function that allows communication to the data broker via inter process communication; a data broker, which orchestrates communication between the emulated control system network and the simulation; an endpoint, which facilitates communication between the data broker and PLC's on the control network using ModBus/TCP; and an example PLC structured text files that work with OpenPLC, an open source emulated PLC. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Hahn, Andrew↗
Empirical modeling for intelligent, real-time manufacture control
Artificial neural systems (ANS), also known as neural networks, are an attempt to develop computer systems that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural networks. The ANS consists of a series of nodes (neurons) and weighted connections (axons) that, when presented with a specific input pattern, can associate specific output patterns. It is essentially a highly complex, nonlinear, mathematical relationship or transform. These constructs have two significant properties that have proven useful to the authors in signal processing and process modeling: noise tolerance and complex pattern recognition. Specifically, the authors have developed a new network learning algorithm that has resulted in the successful application of ANS's to high speed signal processing and to developing models of highly complex processes. Two of the applications, the Weld Bead Geometry Control System and the Welding Penetration Monitoring System, are discussed in the body of this paper.
Xu, Xiaoshu↗