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Results for “control system design”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Control system design for a small pressurized water reactor - 141

Small Pressurized Water Reactors (SPWR) have unique designs from the commercial large Pressurized Water Reactors (PWRs). Integral design is adopted. There are no hot legs and cold legs between the reactor core and the steam generators like in the PWR. Strong interactions exist among different loops. The pressure vessel is large in volume and the coolant inventory is also in a large amount. The inertia of the coolant is large and it takes more time for the primary system to respond to disturbances. The steam generator adopts the once-through design and the water inventory is small. The steam generator is very sensitive to disturbances. These unique characteristics challenge the control system design of SPWR. Relap5 is used to model the SPWR. Steady-state simulation is performed to verify the correctness of the model. In the reactor power control system, both the reactor fission power and the coolant average temperature are regulated by the control rod reactivity. In the feedwater flow control system, the coordination between the reactor and the turbine is considered and coolant average temperature is adopted as one measurable disturbance for the control system. The coolant pressure is adjusted based on the heaters and spray in the pressurizer. The water level in the pressurizer is controlled by the charging flow and the letdown flow is compensated to calculate the charging flow needed. Transient simulations are carried out to evaluate the control system performance. When the reactor is perturbed, the reactor can be stabilized under the control system. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

A Novel Modular, Reconfigurable Battery Energy Storage System: Design, Control, and Experimentation

This paper presents a novel modular, reconfigurable battery energy storage system. The proposed design is characterized by a tight integration of reconfigurable power switches and DC/DC converters. This characteristic enables isolation of faulty cells from the system and allows fine power control for individual cells toward optimal system-level performance. An optimal power management approach is developed to extensively exploit the merits of the proposed design. Based on receding-horizon convex optimization, this approach aims to minimize the total power losses in charging/discharging while allocating the power in line with each cell’s condition to achieve state of-charge (SoC) and temperature balancing. By appropriate design, the approach manages to regulate the power of a cell across its full SoC range and guarantee the feasibility of the optimization problem. Here, we perform extensive simulations and further develop a lab-scale prototype to validate the proposed system design and power management approach.

25 ENERGY STORAGE↗
DOE OSTI2023

Control Systems Design for STS Accelerator

The Second Target Station (STS) Project will expand the capabilities of the existing Spallation Neutron Source (SNS), with a suite of neutron instruments optimized for long wavelengths. A new accelerator transport line will be built to deliver one out of four SNS pulses to the new target station. The Integrated Control Systems (ICS) will provide remote control, monitoring, OPI, alarms, and archivers for the accelerator systems, such as magnets power supply, vacuum devices, and beam instrumentation. The ICS will upgrade the existing Linac LLRF controls to allow independent operation of the FTS and STS and support different power levels of the FTS and STS proton beam. The ICS accelerator controls are in the phase of preliminary design for the control systems of magnet power supply, vacuum, LLRF, Timing, Machine protection system (MPS), and computing and machine network. The accelerator control systems build upon the existing SNS Machine Control systems, use the SNS standard hardware and EPICS software, and take full advantage of the performance gains delivered by the PPU Project at SNS.

Yan, Jay↗
DOE OSTI2018

Control system design and stability analysis for a three phase SiC-based Filter-less grid-connected PV inverter

In this paper, a control system of a filter-less grid-connected SiC inverter is designed. Stability analysis has been researched with a focus on grid disturbance rejection. The analysis shows that the conventional control method with instantaneous grid voltage feedforward (IGVF) will significantly limit the bandwidth or stability margin of a filter-less grid-connected inverter, thus make the inverter sensitive to grid disturbance. Two proposed grid voltage feedforward control methods, which require little additional computation resources, are presented to suppress the grid voltage disturbance. The design methods of control parameters are derived. The effects of the proposed feedforward methods are also compared with that of conventional IGVF. Lastly, the grid-connected experimental results of a three phase SiC based filter-less PV inverter are provided to verify and compare the proposed control methods.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Enabling integrated AI control on DIII-D: a control system design with state-of-the-art experiments

We present the design and application of a general algorithm for Prediction And Control using MAchiNe learning (PACMAN) in DIII-D. Machine learning (ML)-based predictors and controllers have shown great promise in achieving regimes in which traditional controllers fail, such as tearing mode (TM) free scenarios, ELM-free scenarios and stable advanced tokamak conditions. The architecture presented here was deployed on DIII-D to facilitate the end-to-end implementation of advanced control experiments, from diagnostic processing to final actuation commands. This paper describes the detailed design of the algorithm and explains the motivation behind each design point. We also describe several successful ML control experiments in DIII-D using this algorithm, including a reinforcement learning controller targeting advanced non-inductive plasmas, a wide-pedestal quiescent H-mode ELM predictor, an Alfvén Eigenmode controller, a Model Predictive Control plasma profile controller and a state-machine TM predictor-controller. There is also discussion on guiding principles for real-time ML controller design and implementation.

machine learning↗
DOE OSTI2024

Simultaneous optimal system and controller design for multibody systems with joint friction using direct sensitivities

Abstract Real-world multibody systems are often subject to phenomena like friction, joint clearances, and external events. These phenomena can significantly impact the optimal design of the system and its controller. This work addresses the gradient-based optimization methodology for multibody dynamic systems with joint friction using a direct sensitivity approach. The Brown–McPhee model has been used to characterize the joint friction in the system. This model is suitable for the study due to its accuracy for dynamic simulation and its compatibility with sensitivity analysis. This novel methodology supports codesign of the multibody system and its controller, which is especially relevant for applications like robotics and servo-mechanical systems, where the actuation and design are highly dependent on each other. Numerical results are obtained using a software package written in Julia with state-of-the-art libraries for automatic differentiation and differential equations. Three case studies are provided to demonstrate the attractive properties of simultaneous optimal design and control approach for certain applications.

Verulkar, Adwait↗
DOE OSTI2019

Development of a Reference Governor-based Control Scheme for Integrated Energy Systems

The concept of an Integrated Energy System (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. In practice what is achievable is limited by not only the inherent physical response characteristics of individual plant units but also by equipment operating limits. The inherent response characteristics are presently accounted for in the RAVEN-based HYBRID framework by dynamic models for plant units. The equipment operating limits, which are not yet addressed in HYBRID, are the subject of this report. These limits are set to achieve a design service life for a plant unit and are based on material degradation in the presence of mechanical fatigue induced by thermal cycling and by structure creep resulting from elevated temperature conditions. In general, the plant unit designer determines and specifies the allowable operating range of key process variables. It is then up to the integrated system design engineer to ensure those conditions are met. This can be accomplished through a combination of limiting the demand rates made on the plant unit and designing a control system that limits variations of key process variables. The typical control system design procedure, however, is not well suited for achieving this for complex dynamic systems such as encountered in integrated energy systems where multiple plant units must be simultaneously coordinated. This report describes how equipment operating limitations in an IES can be formally met through a control system design procedure know as the Reference Governor. The approach augments the existing controllers in a plant unit with an advance controller that modifies the issued setpoints so that selected process variables remain within limits. The design procedure is applied to the reference multi-unit system that has been the focus of Modeling and Simulation task in the Integrated Energy System program. Results describing application to the problem of limiting key process variables during operational transients for two of the plant units, the balance of plant and the gas turbine, are then presented. It is demonstrated that the Reference Governor method is an effective means for ensuring equipment operating constraints can be met in an IES. The software that implements the method has been made accessible to others on the Modeling and Simulation upload site.

42 ENGINEERING↗
DOE OSTI2023

Control Co-Design of Wind Turbines

Wind energy is recognized worldwide as cost-effective and environmentally friendly, and it is among the fastest-growing sources of electrical energy. To further decrease the cost of wind energy, wind turbines are being designed at ever-larger scales. To expand the deployment of wind energy, wind turbines are also being designed on floating platforms for placement in deep-water locations offshore. Both larger-scale and floating wind turbines pose challenges because of their greater structural loads and deflections. Complex, large-scale systems such as modern wind turbines increasingly require a control co-design approach, whereby the system design and control design are performed in a more integrated fashion. This article reviews recent developments in control co-design of wind turbines. We provide an overview of wind turbine design objectives and constraints, issues in the design of key wind turbine components, modeling of the wind turbine and environment, and controller coupling issues. Wind turbine control functions and the integration of control design in co-design are detailed with a focus on co-design compatible control approaches.

17 WIND ENERGY↗
DOE OSTI2025

Evaluate data lake design for the accelerator control system

Increasing precision in automation for modern particle accelerators not only creates a requirement to gather data from all devices but also demands scalable and high-performance data infrastructure with the capability of handling vast incoming device data. A well architected data lake is suitable for such a system which integrates real-time data acquisition, transient data caching, and long-term storage. This paper evaluates data lake architecture for an Accelerator Control System (ACS), focusing on two critical components of a data lake, data cache and long-term storage.

Jaikar, Amol [Fermilab]↗
DOE OSTI2021

Model based co-simulation platform for integrated building system control and design optimization

Both steady-state and dynamic simulations have been widely used by HVAC&R industry to support product/equipment development for decades. Steady-state simulation focuses on the system mass, energy and momentum balance of an equilibrium state. It is based on high-fidelity components models, and thus is suitable for system and component design optimization. Dynamic simulation studies the system transient response and is generally used for controls development and verification. It usually does not require rigorous component models of high accuracy because 1) the commonly used PID control is feedback control whose control performance evaluation doesn’t require high fidelity system/plant model; 2) high-fidelity dynamic model significantly increases the number of equations and variables and creates tremendous challenge for math solver. For supervisory control, transactive control or optimization of an integrated building system, the HVAC&R equipment is often one of the sub-components to be controlled. High-fidelity equipment models are required for accurately evaluating control strategies. In addition, building equipment manufacturers have developed a lot of high-fidelity steady-state equipment/component models per their expertise. Thus, a platform that can integrate OEM high-fidelity steady-state model with dynamic building simulation and/or electric power system & grid simulation to support the development and verification of supervisory control for integrated building systems is necessary. In this study, ORNL’s heat pump design tool (HPDM) is utilized to develop a co-simulation platform for supervisory control and optimization in integrated building systems. It is based on a model that integrates high-fidelity steady-state simulation equipment models with dynamic building simulation. A practical case of using the proposed co-simulation platform to develop and evaluate the supervisory control and optimization is presented and discussed.

Sun, Jian↗
DOE OSTI2025

Cryogenic Performance of the SPT-SLIM Receiver

The South Pole Telescope Shirokoff Line Intensity Mapper (SPT-SLIM) is a millimeter-wave line-intensity mapping experiment, deployed on the South Pole Telescope (SPT) during the 2024-2025 Austral Summer season. This pathfinder experiment serves to demonstrate the on-sky operation of multi-pixel on-chip spectrometer technology. We present on the cryogenic performance of the SPT-SLIM receiver for this Year 1 observing campaign. The SPT-SLIM receiver utilizes an Adiabatic Demagnetization Referigerator (ADR) for cooling the focal plane of superconducting filterbank spectrometers to a temperature of 150mK. We demonstrate stable thermal performance of the focal plane module during observing operations in line with thermal modelling, enabling a cryogenic operation efficiency above 80%. We also report on the receiver control system design utilizing the Observatory Control System (OCS) platform for automated cryogenic operation on the SPT.

Young, Matthew [Fermilab]↗
DOE OSTI2017

Applicability of available Li-ion battery degradation models for system and control algorithm design

Within electrified vehicle powertrains, lithium-ion battery performance degrades with aging and usage, resulting in a loss in both energy and power capacity. As a result, models used for system design and control algorithm development would ideally capture the impact of those efforts on battery capacity degradation, be computationally efficient, and simple enough to be used for algorithm development. This paper provides an assessment of the state-of-the-art in lithium-ion battery degradation models, including accuracy, computational complexity, and amenability to control algorithm development. Various aging and degradation models have been studied in the literature, including physics-based electrochemical models, semi-empirical models, and empirical models. Some of these models have been validated with experimental data; however, comparisons of pre-existing degradation models across multiple experimental data sets have not been previously published. Three representative models, a 1-d electrochemical model (a combination of performance model and degradation model), a semi-empirical degradation model (the performance is predicted by an equivalent circuit model) and an empirical degradation model (the performance is predicted by an equivalent circuit model), are compared against four published experimental data sets for a 2.3-Ah commercial graphite/LiFePO 4 cell. Based on simulation results and comparisons to experimental data, the key differences in the aging factors captured by each of the models are summarized. Here the results show that the physics-based model is best able to capture results across all four representative data sets with an error less than 10%, but is 20x slower than the empirical model, and 134x slower than the semi-empirical model, making it unsuitable for powertrain system design and model-based algorithm development. Despite being computationally efficient, the semi-empirical and empirical models, when used under conditions that lie outside the calibration data set, exhibit up to 71% error in capacity loss prediction. Such models require expensive experimental data collection to recalibrate for every new application. Thus, in the author’s opinion, there exists a need for a physically-based model that generalizes well across operating conditions, is computationally efficient for model-based design, and simple enough for control algorithm development.

25 ENERGY STORAGE↗
DOE OSTI2022

Design of a supervisory control system for autonomous operation of advanced reactors

Advanced reactors to be deployed in the coming decades will face deregulated energy markets, and may adopt flexible operation to boost profitability. To aid in the transition from baseload to flexible operation paradigm, autonomous operation is sought. This work focuses on the control aspect of autonomous operation. Specifically, a hierarchical control system is designed to support constraint enforcement during routine operational transients. Within the system, data-driven modeling, physics-based state observation, and classical control algorithms are integrated to provide an adaptable and robust solution. A 320 MW Fluoride-cooled High-temperature Pebble-bed Reactor is the design basis for demonstrating the proposed control system. The hierarchical control system consists of a supervisory layer and low-level layer. The supervisory layer receives requests to change the system's operating conditions (e.g., the current reactor power to meet a load -follow), and accepts or rejects them based on constraints that have been assigned. Constraints are issued to keep the plant within an optimal operating region. The low-level layer interfaces with the actuators of the system to fulfill requested changes, while maintaining tracking and regulation duties. Further, to accept requests at the supervisory layer, the Reference Governor algorithm was adopted. To model the dynamics of the reactor, a system identification algorithm, Dynamic Mode Decomposition, was utilized. To estimate the evolution of process variables that cannot be directly measured (e.g., the propagation of delayed neutron precursors), the Unscented Kalman Filter, incorporating a nonlinear model of nuclear dynamics, was adopted. The composition of these algorithms led to a numerical demonstration of constraint enforcement during a 40% power drop transient (at a rate of 5 %/min). Uncontrolled secondary-side temperatures were successfully constrained. Adaptability of the proposed system was demonstrated by modifying the constraint values, and enforcing them during the transient. Robustness was also demonstrated by enforcing constraints under noisy environments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Bridging the Gap Between Modern UX Design and Particle Accelerator Control Room Interfaces

Accelerator control systems often represent relatively complex and safety-sensitive human-machine interfaces within process control industries. These systems are technically robust and reflect the cumulative integration of solutions built and adapted across decades. One of the regular, unfortunate casualties of provisional accelerator control system updates is their human-system interfaces (HSIs) which often lag behind modern usability and design standards. An additional challenge is that although there is a multitude of established human factors (HF), and user experience (UX) principles for everyday digital applications, there are very few (if any) established principles for complex and safety-critical applications for an accelerator. This paper argues for the importance of established HF and UX principles (herein referred to as human-centered design principles) into the development of accelerator HSIs, emphasizing the need for clarity, consistency, responsiveness, and cognitive accessibility. Drawing from HF/UX best practices and human-centered design, this paper discusses how these approaches can enhance operator performance, reduce human error, and improve accelerator personnel collaboration. Case studies from Accelerator Control Operations Research Network (ACORN) at Fermilab are explored to demonstrate how interfaces built with human-centered design principles can scale with system complexity while remaining intuitive and efficient for diverse user roles including operators, machine experts, and engineers. By bridging the gap between traditional control system design and modern human-centered design methods, this paper provides a roadmap for evolving accelerator HSIs into more usable, maintainable, and effective tools.

Hill, Rachael [Idaho Natl. Lab.]↗
DOE OSTI2021

Resonance Control System for the PIP-II IT HWR Cryomodule

The HWR (half-wave-resonator) cryomodule is the first one in the superconducting section of the PIP-II LINAC project at Fermilab. PIP-II IT is a test facility for the project where the injector, warm front-end, and the first two superconducting cryomodules are being tested. The HWR cryomodule comprises 8 cavities operating at a frequency of 162.5 MHz and accelerating beam up to 10 MeV. Resonance control of the cavities is performed with a pneumatically operated slow tuner which compresses the cavity at the beam ports. Helium gas pressure in a bellows mounted to an end wall of the cavity is controlled by two solenoid valves, one on the pressure side and one on the vacuum side. The resonant frequency of the cavity can be controlled in one of two modes. A pressure feedback control loop can hold the cavity tuner pressure at a fixed value for the desired resonant frequency. Alternately, the feedback loop can regulate the cavity tuner pressure to bring the RF detuning error to zero. The resonance controller is integrated into the LLRF control system for the cryomodule. The control system design and performance of the resonance control system are described in this paper.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Design and Performance of the SPT-SLIM Receiver Cryostat

The South Pole Telescope Shirokoff Line Intensity Mapper (SPT-SLIM) is a millimeter-wavelength line-intensity mapping experiment, which was deployed on the South Pole Telescope (SPT) during the 2024-2025 Austral summer season. This pathfinder experiment serves to demonstrate the on-sky operation of multi-pixel on-chip spectrometer technology. We report on the cryogenic performance of the SPT-SLIM receiver for the first year of commissioning observations. The SPT-SLIM receiver utilizes an Adiabatic Demagnetization Refrigerator (ADR) for cooling the focal plane of superconducting filterbank spectrometers to a temperature of 150 mK. We demonstrate stable thermal performance of the focal plane module during observations consistent with thermal modeling, enabling a cryogenic operating efficiency above 80%. We also report on the receiver control system design utilizing the Observatory Control System (OCS) platform for automated cryogenic operation on the SPT.

Young, M. R. [Fermilab; Chicago U., KICP]↗
DOE OSTI2024

Deep Learning-enhanced Block-Diagram Modeling of Solar Power Systems

Data-driven models of power system inverter-based resources are desired to run simulations faster than with detailed electromagnetic transient models, to hide proprietary design details, to support control system design applications, and to aggregate the effects of distributed energy resources. This paper applies a customized Hammerstein Wiener framework to train block diagram models from thousands of electromagnetic transient simulations or experimental test records. The block diagram models integrate with larger grid simulations as voltagecontrolled current sources or current-controlled voltage sources for several simulators. Guidelines for block architecture and training are presented. Three-phase balanced, three-phase unbalanced, and single-phase examples all achieve an acceptable root mean square error of no more than 0.05 per-unit.

Mcdermott, Thomas E. [Private consulting company]↗