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Model based on optimal control theory for characterizing human operator in preview control task to provide reference frame for studying performance value and learning in manual control
The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of 8 mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. During the development of the SLS TVC system, a family of advanced dynamics models were developed to extend and compliment the simplified quasi-linear “simplex” model historically used for flight control design and stability analysis. The importance of these advanced models became increasingly evident after ambient and hot fire testing of the Core Stage, which revealed a number of findings associated with the dynamic response of the TVC integrated system. Test responses suggested that the TVC did not meet its performance specifications and its step and frequency responses exhibited unexpected departures from prior lab tests and modeled behavior. One driving factor for these results was a higher-than-expected degree of coupling between the TVC system, the engine dynamics, and the Core Stage structure. This paper is the third installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. In this paper, a new method of modeling rocket vehicle thrust vectoring servoelastic dynamics is presented. In this approach, the load dynamics are replaced by a detailed finite element model containing both the rigid body and elastic modes. A partitioning technique is used to compute the effective compliance from the modal data and obtain accurate simulation results using a reduced number of generalized coordinates. Coupled backup structure and nozzle attach compliance effects on multiple engines are captured in higher fidelity than with a spring approximation, eliciting novel effects due to the complex load paths involved in the Core Stage structure. Validation of the model is demonstrated using a variety of structural/modal, laboratory, and full-scale hot fire test data.
The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of 8 mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. During the development of the SLS TVC system, a family of advanced dynamics models were developed to extend and compliment the simplified quasi-linear “simplex” model historically used for flight control design and stability analysis. The importance of these advanced models became increasingly evident after ambient and hot fire testing of the Core Stage, which revealed a number of findings associated with the dynamic response of the TVC integrated system. Test responses suggested that the TVC did not meet its performance specifications and its step and frequency responses exhibited unexpected departures from prior lab tests and modeled behavior. One driving factor for these results was a higher-than-expected degree of coupling between the TVC system, the engine dynamics, and the Core Stage structure. This paper is the third installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. In this paper, a new method of modeling rocket vehicle thrust vectoring servoelastic dynamics is presented. In this approach, the load dynamics are replaced by a detailed finite element model containing both the rigid body and elastic modes. A partitioning technique is used to compute the effective compliance from the modal data and obtain accurate simulation results using a reduced number of generalized coordinates. Coupled backup structure and nozzle attach compliance effects on multiple engines are captured in higher fidelity than with a spring approximation, eliciting novel effects due to the complex load paths involved in the Core Stage structure. Validation of the model is demonstrated using a variety of structural/modal, laboratory, and full-scale hot fire test data.
Occupants are the core of the built environment. Traditional Heating, Ventilation, and Air-Conditioning (HVAC) systems operate with predefined schedules and maximum occupancy assumptions with no consideration of specific occupant information. These generalized assumptions usually do not align with the actual demand and result in over-conditioning and occupant discomfort. In recent years, with the aid of Information & Communication Technology (ICT) and Computer Science (CS), it is possible to acquire real-time and accurate occupant information to satisfy the exact thermal requirement through specific HVAC control in one particular built environment. This mechanism is called HVAC “Occupant-centric Control (OCC).” HVAC OCC strategy starts with collecting the occupant’s information (e.g., presence/absence) and then applies it to meet the occupant’s requirement (e.g., thermal comfort). However, even though some research studies and field pilot demonstrations have been devoted to the field of OCC, there is a lack of systematic knowledge about occupant data, which is the principal component of OCC for HVAC researchers and practitioners. To fill this gap, this review paper discusses OCC with a particular emphasis on occupant information and investigates how this information can assist HVAC operation in providing an acceptable built environment in required spaces during the required time. Finally, we provide a fine-grained, comprehensive picture of occupant information, discuss its features, the modalities of information feed-in into the HVAC control, and the application of commonly utilized occupant information for OCC.
In recent years, attacks such as the Stuxnet malware have demonstrated that cyberattacks against control systems cause extensive damage. These attacks can result in physical damage to the networked systems under their control. In this paper, we discuss our approach for detecting such attacks by distinguishing between programs running on a programmable logic controller (PLC) without having to monitor communications. Using power signatures generated by an attached, high-frequency power measurement device, we can identify what a PLC is doing and when an attack may have altered what the PLC should be doing. To accomplish this, we generated labeled data for testing our methods and applied feature engineering techniques and machine learning models. The results of this research demonstrate that Random Forests and Convolutional Neural Networks classify programs with up to 98% accuracy for major program differences and 84% accuracy for minor differences. Our results can be used for both online and offline applications.
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Controlling magnetism in two-dimensional (2D) materials via electric fields and doping enables robust long-range order by providing an external mechanism to modulate magnetic exchange interactions and anisotropy. Here in this report, we predict that transition metal carbide and nitride MXenes are promising candidates for controllable magnetic 2D materials. The surface terminations introduced during synthesis act as chemical dopants that influence the electronic structure, enabling controllable magnetic order. We show ground-state magnetic ordering in Janus M 2 XO x F 2–x (M is an early transition metal, X is carbon or nitrogen, and x = 0.5, 1, or 1.5) with asymmetric surface functionalization, where local structural and chemical disorder induces magnetic ordering in some systems that are nonmagnetic or weakly magnetic in their pristine form. The resulting magnetic states of these noncentrosymmetric structures can be robustly switched and stabilized by tuning the interlayer exchange couplings with small applied electric fields. Furthermore, bond directionality is enhanced by Janus functionalization, resulting in improved magnetic anisotropy, which is essential to stable 2D magnetic ordering. The mixed termination-induced anisotropy leads to robust Ising ferromagnetism with an out-of-plane easy axis over the full range of relevant termination compositions for Janus Mn 2 N. Janus Cr 2 C, V 2 C, and Ti 2 C were found to be robustly antiferromagnetic. Our results provide a strategy for exploiting asymmetric surface functionalization to achieve room-temperature nanoscale magnetism under ambient conditions in MXenes with currently available synthesis techniques.
By constructing a Luenberger-type asymptotic observer, a method of finding the control function, that ensures the translation of a class of nonlinear stationary control systems of ordinary differential equations from the initial state to a given final state taking into account the actual measured values, was developed. A constructive criterion guaranteeing the existence of solution of this problem was found. An algorithm is proposed for constructing a control function that transfer wide class of nonlinear systems of ordinary differential equations from an initial state to an fixed state. The algorithm is convenient for numerical implementation. A constructive condition is obtained for which this transfer is possible.
This work develops a new multi delity ensemble Kalman lter (MFEnKF) algorithm based on linear control variate framework. The approach allows for rigorous multi delity extensions of the EnKF, where the uncertainty in coarser delities in the hierarchy of models represent control variates for the uncertainty in ner delities. Small ensembles of high delity model runs are com- plemented by larger ensembles of cheaper, lower delity runs, to obtain much improved analyses at only small additional computational costs. We investigate the use of reduced order models as coarse delity control variates in the MFEnKF, and provide analyses to quantify the improvements over the traditional ensemble Kalman lters. We apply these ideas to perform data assimilation with a quasi-geostrophic test problem, using direct numerical simulation and a corresponding POD-Galerkin reduced order model. Numerical results show that the two- delity MFEnKF provides better analyses than existing EnKF algorithms at comparable or reduced computational costs.
As a part of the Washington Clean Energy Fund, Avista Utilities has installed a UniEnergy Technologies vanadium redox-flow battery in Pullman, Washington to assess the value it could provide. PNNL is working with Avista to develop a controller for the battery that will maximize the value it provides. This controller will use forecasts for various electrical and financial parameters to define the optimal operating behavior of the battery. As a part of the controller development, PNNL is requesting certain data from Avista; this report outlines this data request.
In recent years, the technical capabilities and requirements for distributed wind turbines to provide ancillary services beyond maximum energy production has increased. Ancillary services, leveraged through advanced wind turbine controls, can support grid stability, reliability, and resilience. In the context of a microgrid, wind turbines can provide ancillary services that are useful in both islanded and grid-connected modes, as demonstrated in previous parts of this report series. This report focuses on how wind turbines with advanced controls and power electronics can support the stability of the microgrid during transitions from grid-connected to island mode, and back. This report documents simulation results from a model of the National Renewable Energy Laboratory (NREL) Flatirons Campus containing NREL's 600-kilowatt Controls Advanced Research Turbine. Using this turbine, we demonstrate through desktop simulation how a wind turbine can support the voltage and frequency of a microgrid during transitions - from making planned transitions seamless to keeping all loads online during some unplanned transitions to supporting black start in the event of an open transition (blackout).
For successful cell research, the growth culture environment must be tightly controlled. Deviance from the optimal conditions will mask the desired variable being analyzed or lead to inconstancies in the results. In standard laboratories, technology and procedures are readily available for the reliable control of variables such as temperature, pH, nutrient loading, and dissolved gases. Due to the nature of spaceflight, and the inherent constraints to engineering designs, these same elements become a challenge to maintain at stable values by both automated and manual approaches. Launch mass, volume, and power usage create significant constraints to cell culture systems; nonetheless, innovative solutions for active environmental controls are available. The acidity of the growth media cannot be measured through standard probes due to the degradation of electrodes and reliance on indicators for chromatography. Alternatively, carbon dioxide sensors are capable of monitoring the pH by leveraging the relationship between the partial pressure of carbon dioxide and carbonic acid in solution across a membrane. In microgravity cell growth systems, the gas delivery system can be used to actively maintain the media at the proper acidity by maintaining a suitable gas mixture around permeable tubing. Through this method, launch mass and volume are significantly reduced through the efficient use of the limited gas supply in orbit.
The study and control of inverted pendulum dynamics is of interest to NASA to better control the stability of a rocket. The different compartments of a rocket can move within a rocket during launch (i.e., rocket fuel slosh) and can affect its overall trajectory. Focusing on the inverted pendulum robot, PENNY, the dynamics are reduced to a simpler model which can prove to be more insightful for deriving more complex models and control laws. From the inverted pendulum bot, we can incorporate complexity into our physical model and approximate to the dynamics of a rocket (i.e., flexible inverted pendulum, multistage pendulum).
The purpose of air traffic control (ATC) is to provide a safe and efficient service for all air traffic. Since its inception, ATC has evolved in response to user needs, achieving exceptionally high standards of safety in a context of shifting complexity and density of air traffic operations. But predicted changes in societal demands, technological advancements and airspace-user needs create new challenges as we look to the mid and far term. This portion of the white paper presents some of the mid and far term visions, out to 2050, for upcoming challenges and changes to air traffic control demands and how Human Factors can support the development of air traffic control to safely and efficiently meet the needs of airspace users.
A study of the potential implementations of localized active flow control (AFC) technology onto future airplanes is presented. This collaborative investigation addresses key objectives of the NASA Advanced Air Transport Technology (AATT) Project, in terms of reduction in fuel consumption and lower emission. It specifically targets the goals set forth in a roadmap developed by the NASA/Boeing team. The roadmap is a result of a series of meetings held between the two parties over the years and it represents a shared vision for practical implementations, leading up to flight demonstrations of localized flow control. If successful, localized flow control may lead to important ramifications for next generation airplanes from both the economic and environmental perspectives. Under this contract localized AFC has been used to improve aerodynamic performance during high-lift operations using Computational Fluid Dynamics (CFD). Specifically, AFC has been applied at the aileron and at various location in the wing leading edge (LE) regions. The applications target reduced drag and enhanced lift over the range of practical angles of attack, including stall. These benefits translate to airplane performance improvements, such as longer range or larger payload. The CFD results are used to quantify potential aerodynamic benefits, as well as the input required for actuation. This helps identify the most promising candidates, which potentially provide material net airplane level enhancements using onboard fluidic sources. The airplane configuration selected for the CFD study is a representative of a future short/medium-range twin-engine airplane dubbed the Reference Aircraft. A slew of AFC applications has been explored and their aerodynamic performance enhancements were benchmarked against the baseline Reference Aircraft. Promising AFC candidates have been deemed practical and potentially suitable for both the aileron and the wing LE implementations. The findings on the Reference Aircraft are used to guide the development of the AFC-enhanced aileron for the CRM-HL. The wind-tunnel model of the CRM-HL will be used by NASA to validate the AFC concepts, complementing the CFD-based analysis and the integration study (final report document #3).