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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 505 records · Page 28
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Examination of Unified Control Incorporating Generalized Control Allocation

Hybrid vehicles which combine vertical take off and landing with cruise configurations pose a unique challenge for control design and implementation. For this class of vehicle, successful control designs have historically broken the flight envelope into phases of flight and modified the control approach for each phase. This research approaches control in a unified way across the entire envelope utilizing a robust optimal design which provides effect or weighting then implemented in a generalized Affine Generalized Inverse control allocation algorithm. System performance for a Lift plus Cruise class vehicle is presented.

Unified Control,Control Allocation↗
DOE OSTI2016

Migration of Older to New Digital Control Systems in Nuclear Power Plant Main Control Rooms

The United States (U.S.) Department of Energy (DOE) Office of Nuclear Energy (NE) has the primary mission to advance nuclear power by resolving socio-technical issues through research and development (R&D). One DOE-NE activity supporting this mission is the Light Water Reactor Sustainability (LWRS) program. LWRS has the overall objective to sustain the operation of existing commercial nuclear power plants (NPPs) through conducting R&D across multiple “pathways,” or R&D focus areas. The Advanced Instrumentation, Information, and Control (II&C) Systems Technologies pathway conducts targeted R&D to address aging and reliability concerns with the legacy instrumentation and control (I&C) and related information systems in operating U.S. NPPs. This work involves (1) ensuring that legacy analog II&C systems are not life-limiting issues for the LWR fleet, and (2) implementing digital II&C technology in a manner that enables broad innovation and business improvement in the NPP operating model. Under the LWRS Advanced II&C pathway, Human Factors experts at Idaho National Laboratory (INL) have been conducting R&D in support of NPP main control room (MCR) modernization activities. Work in prior years has focused on migrating analog I&C systems to new digital I&C systems (). In fiscal year 2016 (FY16), one new focus area for this research is migrating older digital I&C systems to new and advanced digital I&C systems. This report summarizes a plan for conducting a digital-to-digital migration of a legacy digital I&C system to a new digital I&C system in support of control room modernization activities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Controlling Rheology of Fluid Interfaces through Microblock Length of Sequence-Controlled Amphiphilic Copolymers

Previous studies have demonstrated that films of sequence-controlled amphiphilic copolymers display contact angles that depend on microblock size. This suggests that microblock length may provide a means of tuning surface and interfacial properties. In this work, the interfacial rheology of a series of sequence-controlled copolymers, prepared through the addition of bicyclo[4.2.0]oct-1(8)-ene-8-carboxamide (monomer A) and cyclohexene (monomer B) to generate sequences up to 24 monomeric units composed of (A m B n ) i microblocks, where m, n, and i range from 1 to 6. Interfacial rheometry is used to measure the mechanical properties of an air–water interface with these copolymers. As the microblock size increases, the interfacial storage modulus, G', increases, which may be due to an increase in the size of interfacial hydrophobic domains. Small-angle X-ray scattering shows that the copolymers have a similar conformation in solution, suggesting that any variations in the mechanics of the interface are due to assembly at the interface, and not on solution association or bulk rheological properties. This is the first study demonstrating that microblock size can be used to control interfacial rheology of amphiphilic copolymers. Here, the results provide a new strategy for controlling the dynamics of fluid interfaces through precision sequence-controlled polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The wave energy converter control competition (WECCCOMP): Wave energy control algorithms compared in both simulation and tank testing

The wave energy control competition established a benchmark problem which was offered as an open challenge to the wave energy system control community. The competition had two stages: In the first stage, competitors used a standard wave energy simulation platform (WEC-Sim) to evaluate their controllers while, in the second stage, competitors were invited to test their controllers in a real-time implementation on a prototype system in a wave tank. The performance function used was based on converted energy across a range of standard sea states, but also included aspects related to economic performance, such as peak/average power, peak force, etc. This paper compares simulated and experimental results and, in particular, examines if the results obtained in a linear system simulation are borne out in reality. Overall, within the scope of the device tested, the range of sea states employed, and the performance metric used, the conclusion is that high-performance WEC controllers work well in practice, with good carry-over from simulation to experimentation. However, the availability of a good WEC mathematical model is deemed to be crucial.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Robust cooperative control strategy for a platoon of connected and autonomous vehicles against sensor errors and control errors simultaneously in a real-world driving environment

In a real-world driving environment, a platoon of connected and autonomous vehicles (CAVs) is subject to many internal and external disturbances, resulting in uncertain vehicle dynamics. In general, the disturbances can be categorized into two types: disturbances due to vehicle sensor errors (e.g., GPS error) and disturbances due to vehicle control errors (e.g., actuator delay). In the literature, many control strategies have been proposed to improve the robustness of the CAV platoon against uncertain vehicle dynamics induced by these disturbances. However, most of these strategies only consider one type of disturbance and cannot tackle both types of disturbances simultaneously. Furthermore, they are designed to maximize the benefits of each vehicle in the platoon independently, which can deteriorate the performance of the platoon. Here, to address these problems, this study proposes a robust cooperative control (RCC) strategy to maneuver the vehicles in the platoon cooperatively to counteract the impacts of both types of disturbances. The RCC strategy is developed based on a minimax problem, where the maximization subproblem seeks to find the worst inputs for the uncertainty terms in the vehicle dynamics equation to minimize the platoon performance, while the minimization subproblem seeks to find the optimal control decisions for all subsequent vehicles to maximize the platoon performance in the worst case. To solve the minimax problem, this study proposes a globally convergent solution algorithm. It can solve the minimax problem very efficiently to enable real time deployment of the RCC strategy. Numerical application indicates that compared to the existing methods, the RCC strategy can dramatically improve the robustness of the CAV platoon against the uncertain vehicle dynamics induced by both vehicle state detection errors and vehicle control errors. Therefore, it can maneuver the CAV platoon safely and efficiently in a real-world driving environment.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Engineering microbial consortia for controllable outputs

Much research has been invested into engineering microorganisms to perform desired biotransformations; nonetheless, these efforts frequently fall short of expected results due to the unforeseen effects of biofeedback regulation and functional incompatibility. In nature, metabolic function is compartmentalized into diverse organisms assembled into resilient consortia, in which the division of labor is thought to lead to increased community efficiency and productivity. Here, we consider whether and how consortia can be designed to perform bioprocesses of interest beyond the metabolic flexibility limitations of a single organism. Advances in post-genomic analysis of microbial consortia and application of high-resolution global measurements now offer the promise of systems-level understanding of how microbial consortia adapt to changes in environmental variables and inputs of carbon and energy. We argue that when combined with appropriate modeling framework that predictive knowledge generates testable hypotheses and orthogonal synthetic biology tools, such understanding can dramatically improve our ability to control the fate and functioning of consortia. In this article, we articulate our collective perspective on the current and future state of microbial community engineering and control while placing specific emphasis on ecological principles that promote control over community function and emergent properties.

controllable outputs↗
DOE OSTI2019

Control of formation of viscoelastic droplets and distribution of nano-inclusions in functional deposition for lithium–sulfur batteries

The electrospray process produces micro/nanodroplets for various applications such as thin and uniform coatings, drug carriers and mass spectrometry. In this paper, we study the spray processes of viscoelastic jets using simulations and experiments. In discretized modeling, the jet is perturbed with axisymmetric instability and the growth of this instability causes the jet to break into droplets. For the experiments, a solution of polyvinyl alcohol in water is sprayed and is visualized using a high-speed camera. The droplet size distribution is studied from simulations with experiments for three spray cases: electrospray, air spray, and air-controlled electrospray. Our simulations and experiments reveal that the electric field is effective in reducing the droplet size, while air flow offers more jet break-ups and thus a larger number of droplets. As a result, air-controlled electrospray where these two driving forces are synergistically combined leads to a larger number of smaller droplets than electrospray or air spray. As a result, we applied three spray processes to obtain a deposition of sulfur/mesoporous carbon/graphene/polymer binder composites as a lithium sulfur battery cathode and demonstrated that air-controlled electrospray leads to a higher capacity and rate capability than other processes, exhibiting 800 mA h g –1 at 0.5C and 600 mA h g –1 at 2C.

25 ENERGY STORAGE↗
DOE OSTI2015

Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights

This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in the closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Traffic Signal Control for Large-Scale Urban Traffic Networks: Real-World Experiments using Vision-Based Sensors

Effective control of traffic signals plays a critical role in ensuring smooth vehicle flow in urban areas. Expertly engineered traffic signal controllers can considerably minimize travel delays and enhance sustainability. In this paper, the team proposes the Model Predictive Control (MPC) traffic signal control strategy using real-time traffic flow data from a vision-based camera as feedback information. Also, a realistic signal timing plan that considers National Electrical Manufacturers Association (NEMA) constraints has been developed to be applied to real-world scenarios. The primary aim is to reduce the number of vehicles across all links in the controlled area, thereby optimizing traffic flow and reducing energy consumption. To validate the proposed method, several real-life experiments were conducted at 24 intersections in Chattanooga, Tennessee, by collaborating with traffic field engineers. These experiments demonstrated significant performance improvements in comparison to the existing method.

data processing↗
DOE OSTI2021

Phasor Based Control with the Distributed, Extensible Grid Control Platform

This paper describes how to implement Phasor Based Control (PBC) using the Distributed, Extensible Grid Control (DEGC) Platform. PBC is a novel method for controlling distributed energy resources (DER) that coordinates a centralized optimization with distributed feedback controllers to enforce voltage phasor targets. DEGC is an open source software and communication platform designed for general DER control. We deployed PBC at Lawrence Berkeley Lab's FLEXLAB test site, conducting multiple hardware-in-the-loop test runs. Here, we describe how DEGC was used to implement PBC on hardware, and results demonstrating successful deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Fuzzy Controllers in the Adaptive Control System of a CNC Lathe

Traditional approaches to improving the technological system of CNC metal-cutting machines include increasing the rigidity, periodic maintenance and repair of its components, and operating at lower speeds. In practice, the most economical approach is stabilization of the inputs to the system. The development of adaptive control systems with stabilization of the cutting forces improves the precision and quality of machining in CNC metal-cutting machines, the productivity, and tool life. However, classical PID controllers are only effective in stabilizing the cutting forces in such systems if continuous real-time parameter adjustment is possible. That sharply increases the complexity of the controller. A new mathematical apparatus based on artificial intelligence (including fuzzy logic) permits the solution of adaptive control problems that previously could hardly even be formulated. The present work addresses the use of fuzzy logic in automatic stabilization of the cutting force for CNC lathes. Simulation of a fuzzy controller shows that this approach to automatic stabilization of the cutting force increases the machining efficiency on existing equipment with indeterminacy in the characteristics of the cutting system and the working environment.

42 ENGINEERING↗
NASA NTRS1957

Experimental Investigation of Temperature Feedback Control Systems Applicable to Turbojet-engine Control

Temperature - fuel-flow and temperature-area feedback control systems were investigated as means of controlling tailpipe gas temperature of a turbojet engine during transient operation in the high-speed region. Proportional-plus-integral control was used in both systems, but in the temperature-area control system it was necessary to add nonlinear components to the basic proportional-plus-integral control to provide satisfactory transient response to a desired step increase in temperature. Time integral of temperature-error functions were used as criteria for determining optimum transient response. A description of engine dynamics was obtained from frequency-response data.

ENGINES, TURBOJET↗
NASA NTRS2016

Task Demand Variation in Air Traffic Control: Implications for Controller Workload, Fatigue, and Performance

In air traffic control, task demand and workload have important implications for the safety and efficiency of air traffic, and remain dominant considerations. Within air traffic control, task demand is dynamic. However, research on demand transitions and subsequent controller perception and performance is limited. This research uses an air traffic control simulation to investigate the effect of task demand transitions, and the direction of those transitions, on workload and fatigue and one efficiency performance measure. Results indicate that a change in task demand appears to affect both workload and fatigue ratings, although not necessarily performance. In addition, participants workload and fatigue ratings in equivalent task demand periods appear to change depending on the demand period preceding the time of the current ratings. Further research is needed to enhance understanding of demand transition and workload history effects on operator experience and performance, in both air traffic control and other safety-critical domains.

workload history↗
DOE OSTI2015

Field Testing of LIDAR-Assisted Feedforward Control Algorithms for Improved Speed Control and Fatigue Load Reduction on a 600-kW Wind Turbine: Preprint

A severe challenge in controlling wind turbines is ensuring controller performance in the presence of a stochastic and unknown wind field, relying on the response of the turbine to generate control actions. Recent technologies such as LIDAR, allow sensing of the wind field before it reaches the rotor. In this work a field-testing campaign to test LIDAR Assisted Control (LAC) has been undertaken on a 600-kW turbine using a fixed, five-beam LIDAR system. The campaign compared the performance of a baseline controller to four LACs with progressively lower levels of feedback using 35 hours of collected data.

17 WIND ENERGY↗