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At least 73 records · Page 4

A Novel Secondary Frequency Regulation with Optimal Priority Selection of AGC Contributions

Automatic generation control (AGC) is used to maintain acceptable frequencies during operation owing to fluctuations in load and variable resources. In conventional industry applications, the AGC signal is allocated to each generator according to the predispatched frequency regulation capacity or the order of economic efficiency. However, with the increasing integration of inverter-based resources (IBRs), the retirement of conventional synchronous generators (SGs) has posed new challenges to frequency control schemes because fewer of them are optional for AGC regulation. In this paper, we propose a novel model predictive control (MPC)-based frequency regulation model to reduce control cost and ensure stability, by considering different critical dynamic factors when optimally selecting the AGC units. The proposed control model – developed in a general form – comprehensively embeds characteristics such as generator ramping rates, reserve capacity, and operation cost. The model predictive control–based two-timescale AGC scheme enhances the capability of immunizing the power disturbance from types of resources by coordinating the control signals between faster IBRs and slower SGs. The case study’s proposed model is verified to be effective in synergistically enforcing different dynamic properties of AGC units into the frequency regulation scheme.

Jiang, Sufan [The University of North Carolina at ↗

Exceptional enhancement of mechanical properties in high-entropy alloys via thermodynamically guided local chemical ordering

Understanding the local chemical ordering propensity in random solid solutions, and tailoring its strength, can guide the design and discovery of complex, paradigm-shifting multicomponent alloys. First, we present a simple thermodynamic framework, based solely on binary enthalpies of mixing, to select optimal alloying elements to control the nature and extent of chemical ordering in high-entropy alloys (HEAs). Next, we couple high-resolution electron microscopy, atom probe tomography, hybrid Monte-Carlo, special quasirandom structures, and density functional theory calculations to demonstrate how controlled additions of Al and Ti and subsequent annealing drive chemical ordering in nearly random equiatomic face-centered cubic CoFeNi solid solution. We establish that short-range ordered domains, the precursors of long-range ordered precipitates, inform mechanical properties. Specifically, a progressively increasing local order boosts the tensile yield strengths of the parent CoFeNi alloy by a factor of four while also substantially improving ductility, which breaks the so-called strength–ductility paradox. Finally, we validate the generality of our approach by predicting and demonstrating that controlled additions of Al, which has large negative enthalpies of mixing with the constituent elements of another nearly random body-centered cubic refractory NbTaTi HEA, also introduces chemical ordering and enhances mechanical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

Barlow, Jonathan Spencer↗

Data-Based Predictive Control with Multirate Prediction Step

Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

Barlow, Jonathan S.↗

LASTRAC.3d: Transition Prediction in 3D Boundary Layers

Langley Stability and Transition Analysis Code (LASTRAC) is a general-purpose, physics-based transition prediction code released by NASA for laminar flow control studies and transition research. This paper describes the LASTRAC extension to general three-dimensional (3D) boundary layers such as finite swept wings, cones, or bodies at an angle of attack. The stability problem is formulated by using a body-fitted nonorthogonal curvilinear coordinate system constructed on the body surface. The nonorthogonal coordinate system offers a variety of marching paths and spanwise waveforms. In the extreme case of an infinite swept wing boundary layer, marching with a nonorthogonal coordinate produces identical solutions to those obtained with an orthogonal coordinate system using the earlier release of LASTRAC. Several methods to formulate the 3D parabolized stability equations (PSE) are discussed. A surface-marching procedure akin to that for 3D boundary layer equations may be used to solve the 3D parabolized disturbance equations. On the other hand, the local line-marching PSE method, formulated as an easy extension from its 2D counterpart and capable of handling the spanwise mean flow and disturbance variation, offers an alternative. A linear stability theory or parabolized stability equations based N-factor analysis carried out along the streamline direction with a fixed wavelength and downstream-varying spanwise direction constitutes an efficient engineering approach to study instability wave evolution in a 3D boundary layer. The surface-marching PSE method enables a consistent treatment of the disturbance evolution along both streamwise and spanwise directions but requires more stringent initial conditions. Both PSE methods and the traditional LST approach are implemented in the LASTRAC.3d code. Several test cases for tapered or finite swept wings and cones at an angle of attack are discussed.

Chang, Chau-Lyan↗

Experimental Aerodynamic Characteristics of the Pegasus Air-Launched Booster and Comparisons with Predicted and Flight Results

Experimental longitudinal and lateral-directional aerodynamic characteristics were obtained for the Pegasus and Pegasus XL configurations over a Mach number range from 1.6 to 6 and angles of attack from -4 to +24 degrees. Angle of sideslip was varied from -6 to +6 degrees, and control surfaces were deflected to obtain elevon, aileron, and rudder effectiveness. Experimental data for the Pegasus configuration are compared with engineering code predictions performed by Nielsen Engineering & Research, Inc. (NEAR) in the aerodynamic design of the Pegasus vehicle, and with results from the Aerodynamic Preliminary Analysis System (APAS) code. Comparisons of experimental results are also made with longitudinal flight data from Flight #2 of the Pegasus vehicle. Results show that the longitudinal aerodynamic characteristics of the Pegasus and Pegasus XL configurations are similar, having the same lift-curve slope and drag levels across the Mach number range. Both configurations are longitudinally stable, with stability decreasing towards neutral levels as Mach number increases. Directional stability is negative at moderate to high angles of attack due to separated flow over the vertical tail. Dihedral effect is positive for both configurations, but is reduced 30-50 percent for the Pegasus XL configuration because of the horizontal tail anhedral. Predicted longitudinal characteristics and both longitudinal and lateral-directional control effectiveness are generally in good agreement with experiment. Due to the complex leeside flowfield, lateral-directional characteristics are not as well predicted by the engineering codes. Experiment and flight data are in good agreement across the Mach number range.

Rhode, M. N.↗

Optically addressed spatial light modulators by MBE-grown nipi MQW structures

Promising approaches for achieving optically addressed spatial light modulators (O-SLMs) are investigated based on combining nipi and multiple quantum well structures. Theoretical aspects of photooptic effects achievable in such structures are treated. Test structures are grown by molecular beam epitaxy using two material systems. (In,Ga)As/GaAs and (Al,Ga)As/GaAs. Experiments show large optically controlled modulation of the absorption coefficient in the quantum well layers, a log power dependence on the control signal, millisecond and shorter time response, and generally predictable behavior. The results are encouraging for several different O-SLM device structures proposed.

Maserjian, Joseph↗

Unsteady Aerodynamic Modeling in Roll for the NASA Generic Transport Model

Reducing the impact of loss-of-control conditions on commercial transport aircraft is a primary goal of the NASA Aviation Safety Program. One aspect in developing the supporting technologies is to improve the aerodynamic models that represent these adverse conditions. Aerodynamic models appropriate for loss of control conditions require a more general mathematical representation to predict nonlinear unsteady behaviors. In this paper, a more general mathematical model is proposed for the subscale NASA Generic Transport Model (GTM) that covers both low and high angles of attack. Particular attention is devoted to the stall region where full-scale transports have demonstrated a tendency for roll instability. The complete aerodynamic model was estimated from dynamic wind-tunnel data. Advanced computational methods are used to improve understanding and visualize the flow physics within the region where roll instability is a factor.

Murphy, Patrick C.↗

Roll Damping Derivatives from Generalized Lifting-Surface Theory and Wind Tunnel Forced-Oscillation Tests

Improving aerodynamic models for adverse loss-of-control conditions in flight is an area being researched under the NASA Aviation Safety Program. Aerodynamic models appropriate for loss of control conditions require a more general mathematical representation to predict nonlinear unsteady behaviors. As more general aerodynamic models are studied that include nonlinear higher order effects, the possibility of measurements that confound aerodynamic and structural responses are probable. In this study an initial step is taken to look at including structural flexibility in analysis of rigid-body forced-oscillation testing that accounts for dynamic rig, sting and balance flexibility. Because of the significant testing required and associated costs in a general study, it makes sense to capitalize on low cost analytical methods where possible, especially where structural flexibility can be accounted for by a low cost method. This paper provides an initial look at using linear lifting surface theory applied to rigid-body aircraft roll forced-oscillation tests.

Pototzky, Anthony S↗

Comparison of simulator fidelity model predictions with in-simulator evaluation data

A full factorial in simulator experiment of a single axis, multiloop, compensatory pitch tracking task is described. The experiment was conducted to provide data to validate extensions to an analytic, closed loop model of a real time digital simulation facility. The results of the experiment encompassing various simulation fidelity factors, such as visual delay, digital integration algorithms, computer iteration rates, control loading bandwidths and proprioceptive cues, and g-seat kinesthetic cues, are compared with predictions obtained from the analytic model incorporating an optimal control model of the human pilot. The in-simulator results demonstrate more sensitivity to the g-seat and to the control loader conditions than were predicted by the model. However, the model predictions are generally upheld, although the predicted magnitudes of the states and of the error terms are sometimes off considerably. Of particular concern is the large sensitivity difference for one control loader condition, as well as the model/in-simulator mismatch in the magnitude of the plant states when the other states match.

Parrish, R. V.↗

Cabin Noise Control for Twin Engine General Aviation Aircraft

An analytical model based on modal analysis was developed to predict the noise transmission into a twin-engine light aircraft. The model was applied to optimize the interior noise to an A-weighted level of 85 dBA. To achieve the required noise attenuation, add-on treatments in the form of honeycomb panels, damping tapes, acoustic blankets, septum barriers and limp trim panels were added to the existing structure. The added weight of the noise control treatment is about 1.1 percent of the total gross take-off weight of the aircraft.

Vaicaitis, R.↗

Results of tests to determine the aerodynamic characteristics of two potential aeromaneuvering orbit-to-orbit shuttle (AMOOS) vehicle configurations in the NASA-Ames 3.5 foot hypersonic wind tunnel

An aerodynamic wind tunnel investigation was conducted in the NASA-Ames Research Center (ARC) 3.5-foot hypersonic facility to provide data for use in obtaining experimental force and static stability characteristics of two potential aeromaneuvering orbit-to-orbit shuttle (AMOOS) vehicle configurations. The experimental data were compared with the aerodynamic characteristics estimated using Newtonian theory, thus establishing the usefulness of these predictions. The candidate AMOOS configurations selected for the wind tunnel tests were the AMOOS 5B and HB configurations. Two flap configurations were tested for each candidate - a forward or compression surface flap and an aft or expansion flap. Photographs and sketches of the two configurations with different control surfaces are shown. It was determined that Newtonian theory generally predicted the aerodynamics of the 5B configuration with acceptable accuracy for all expansion flap deflections and for compression flap deflections less than or equal to 10 degrees. Flow separation upstream of large compression flap deflections was detected from the experimental data.

Ketter, F. C., Jr.↗

Experimental Validation of L1 Adaptive Control: Rohrs' Counterexample in Flight

The paper presents new results on the verification and in-flight validation of an L1 adaptive flight control system, and proposes a general methodology for verification and validation of adaptive flight control algorithms. The proposed framework is based on Rohrs counterexample, a benchmark problem presented in the early 80s to show the limitations of adaptive controllers developed at that time. In this paper, the framework is used to evaluate the performance and robustness characteristics of an L1 adaptive control augmentation loop implemented onboard a small unmanned aerial vehicle. Hardware-in-the-loop simulations and flight test results confirm the ability of the L1 adaptive controller to maintain stability and predictable performance of the closed loop adaptive system in the presence of general (artificially injected) unmodeled dynamics. The results demonstrate the advantages of L1 adaptive control as a verifiable robust adaptive control architecture with the potential of reducing flight control design costs and facilitating the transition of adaptive control into advanced flight control systems.

Xargay, Enric↗

Computational Analysis of Dual Radius Circulation Control Airfoils

The goal of the work is to use multiple codes and multiple configurations to provide an assessment of the capability of RANS solvers to predict circulation control dual radius airfoil performance and also to identify key issues associated with the computational predictions of these configurations that can result in discrepancies in the predicted solutions. Solutions were obtained for the Georgia Tech Research Institute (GTRI) dual radius circulation control airfoil and the General Aviation Circulation Control (GACC) dual radius airfoil. For the GTRI-DR airfoil, two-dimensional structured and unstructured grid computations predicted the experimental trend in sectional lift variation with blowing coefficient very well. Good code to code comparisons between the chordwise surface pressure coefficients and the solution streamtraces also indicated that the detailed flow characteristics were matched between the computations. For the GACC-DR airfoil, two-dimensional structured and unstructured grid computations predicted the sectional lift and chordwise pressure distributions accurately at the no blowing condition. However at a moderate blowing coefficient, although the code to code variation was small, the differences between the computations and experiment were significant. Computations were made to investigate the sensitivity of the sectional lift and pressure distributions to some of the experimental and computational parameters, but none of these could entirely account for the differences in the experimental and computational results. Thus, CFD may indeed be adequate as a prediction tool for dual radius CC flows, but limited and difficult to obtain two-dimensional experimental data prevents a confident assessment at this time.

Lee-Rausch, E. M.↗

Virtual Tokamak for Test and Development of Plasma Control Applied to NSTX-U

Safe and efficient operation of tokamak experiments depends on shot preparation prior to the experiment to maximize performance and avoid issues that are predictable consequences of known physics. The General Atomics TokSys toolbox is used to test and develop the plasma control system (PCS) on numerous tokamaks around the world. Tokamaks that use a version of the DIII-D PCS can connect it to a TokSys simulation and control a virtual version of the tokamak with the real PCS. Recent upgrades to the simulation include more detailed profile and transport modeling to support design and implementation of optimized scenarios. The simulation combines a module called “Profiles” that simulates the 1D profiles of density, pressure, and current and a module called “GSevolve'' that evolves the 2D Grad-Shafranov equilibrium. The “Profiles'' module primarily uses simplified models for fueling, heating, and current. The TRANSP code provides precomputed diffusion coefficients and heating/current drive profiles from radio-frequency and neutral beam sources for the scenarios being simulated. The fidelity of a simulation can be enhanced by analyzing it with TRANSP and making corrections to the precomputed values and iterating until convergence. Simulations of the National Spherical Torus Upgrade (NSTX-U) are presented. It is shown that the simulation reproduces the experimental profile evolution. Here, the simulation has also been upgraded to reproduce the experimental outcome at points of bifurcation. This is demonstrated with a simulation of vertical displacement in NSTX-U.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

GVE-Based Dynamics and Control for Formation Flying Spacecraft

Formation flying is an enabling technology for many future space missions. This paper presents extensions to the equations of relative motion expressed in Keplerian orbital elements, including new initialization techniques for general formation configurations. A new linear time-varying form of the equations of relative motion is developed from Gauss Variational Equations and used in a model predictive controller. The linearizing assumptions for these equations are shown to be consistent with typical formation flying scenarios. Several linear, convex initialization techniques are presented, as well as a general, decentralized method for coordinating a tetrahedral formation using differential orbital elements. Control methods are validated using a commercial numerical propagator.

Breger, Louis↗

Data-Driven Model Predictive Control for Temperature Management of Heat Pipe Microreactor

To enable the self-regulating capability of heat pipe (HP) microreactors, an anticipatory control strategy through model predictive control (MPC) could proactively respond to potential disturbances and deviations in operating setpoints. However, a key factor prohibiting the widespread adoption of MPCs in nuclear applications is the effort and computational costs associated with learning and calibrating first-principles-based process models when the target system is complex and when there are gaps between modeled and target reactor systems. In this paper, we demonstrate data-driven MPC using three approaches for modeling the system dynamics, including a linear state-space model, feedforward neural network, and recurrent neural networks long short-term memory. We present the development and validation process of each model and compare the performance of data-driven MPCs in controlling the temperatures of selected HPs at the evaporator and condenser regions in a 37-HP-monolith system. Our results show that, qualitatively, all data-driven MPCs are producing similar control actions, while quantitatively, with artificial neural nets (especially feedforward neural nets), MPC can better follow drastic changes in setpoints with smallest errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Curriculum-based Reinforcement Learning for Distribution System Critical Load Restoration

This paper focuses on the critical load restoration problem in distribution systems following major outages. To provide fast online response and optimal sequential decision-making support, a reinforcement learning (RL) based approach is proposed to optimize the restoration. Due to the complexities stemming from the large policy search space, renewable uncertainty, and nonlinearity in a complex grid control problem, directly applying RL algorithms to train a satisfactory policy requires extensive tuning to be successful. To address this challenge, this paper leverages the curriculum learning (CL) technique to design a training curriculum involving a simpler steppingstone problem that guides the RL agent to learn to solve the original hard problem in a progressive and more effective manner. We demonstrate that compared with direct learning, CL facilitates controller training to achieve better performance. To study realistic scenarios where renewable forecasts used for decision-making are in general imperfect, the experiments compare the trained RL controllers against two model predictive controllers (MPCs) using renewable forecasts with different error levels and observe how these controllers can hedge against the uncertainty. Results show that RL controllers are less susceptible to forecast errors than the baseline MPCs and can provide a more reliable restoration process.

24 POWER TRANSMISSION AND DISTRIBUTION↗