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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 631 records · Page 35

Online Bayesian State Estimation for Real-Time Monitoring of Growth Kinetics in Thin Film Synthesis

Rapid validation of newly predicted materials through autonomous synthesis requires real-time adaptive control methods that exploit physics knowledge, a capability that is lacking in most systems. Here, in this study, we demonstrate an approach to enable real-time control of thin film synthesis by combining in situ optical diagnostics with a Bayesian state estimation method. We developed a physical model for film growth and applied the direct filter (DF) method for real-time estimation of nucleation and growth rates during pulsed laser deposition (PLD). We validated the approach using simulated and experimental reflectivity data for WSe 2 growth and ultimately deployed the algorithm on an autonomous PLD system during the growth of 1T'-MoTe 2 . The DF robustly estimates growth parameters in real time at early stages of growth, down to 15% monolayer area coverage. This fusion of in situ diagnostics, data assimilation, and physical modeling opens new opportunities in adaptive control of synthesis trajectories toward desired material states.

36 MATERIALS SCIENCE↗

Controlling colloidal crystals via morphing energy landscapes and reinforcement learning

We report a feedback control method to remove grain boundaries and produce circular shaped colloidal crystals using morphing energy landscapes and reinforcement learning–based policies. We demonstrate this approach in optical microscopy and computer simulation experiments for colloidal particles in ac electric fields. First, we discover how tunable energy landscape shapes and orientations enhance grain boundary motion and crystal morphology relaxation. Next, reinforcement learning is used to develop an optimized control policy to actuate morphing energy landscapes to produce defect-free crystals orders of magnitude faster than natural relaxation times. Morphing energy landscapes mechanistically enable rapid crystal repair via anisotropic stresses to control defect and shape relaxation without melting. This method is scalable for up to at least N = 10 3 particles with mean process times scaling as N 0.5 . Further scalability is possible by controlling parallel local energy landscapes (e.g., periodic landscapes) to generate large-scale global defect-free hierarchical structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flight tests of the Digital Integrated Automatic Landing System (DIALS)

The design, development, implementation and flight tests of the Digital Integrated Automatic Landing System (DIALS) are discussed. The system was implemented and flight tested on the Transport Systems Research Vehicle (TSRV), a Boeing 737-100. The design uses modern optimal control methods. The direct digital design obtained uses a 10 Hz rate for the sampling of sensors and the control commands. The basic structure of the control law consists of a steady state Kalman filter followed by a control gain matrix. The sensor information used includes Microwave Landing System (MLS) position, attitude, calibrated airspeed, and body accelerations. The phases of the final approach considered are localized and steep glideslope capture (which may be performed simultaneously or independently), localizer and glideslope track, crab/decrab, and flare to touchdown. The system can capture, track, and flare from conventional, as well as steep, glideslopes ranging from 2.5 deg to 5.5 deg. All of the modes of the control law including the Kalman filters were implemented on the TSRV flight computers which use fixed point arithmetic with 16 bit words. The implementation considerations are described as well as an analysis of the flight test results.

Halyo, N.↗

Robot arm force control through system linearization by nonlinear feedback

Based on a differential geometric feedback linearization technique for nonlinear time-varying systems, a dynamic force control method for robot arms is developed. It uses active force-moment measurements at the robot wrist. The controller design fully incorporate the robot-arm dynamics and is so general that it can be reduced to pure position control, hybrid position/force control, pure force control. The controller design is independent of the tasks to be performed. Computer simulations show that the controller improves the position error by a factor of ten in cases in which position errors generate force measurements. A theorem on linearization of time-varying system is also presented.

Tarn, T. J.↗

The Hubble Space Telescope nickel-hydrogen battery design

Details are presented of the HST (Hubble Space Telescope) battery cell, battery package, and module mechanical and electrical designs. Also included are a summary of acceptance, qualification, and vibration tests and thermal vacuum testing. Unique details of battery cell charge retention performance characteristics associated with prelaunch hold conditions are discussed. Special charge control methods to minimize thermal dissipation during pad charging operations are summarized. This module design meets all NASA fracture control requirements for manned missions.

Nawrocki, D. E.↗

Control systems and methods to enable autonomous drilling

A system or method for drilling includes autonomously controlling a rotary or percussive drilling process as it transitions through multiple materials with very different dynamics. The method determines a drilling medium based on real-time measurements and comparison to prior drilling data, and identifies the material type, drilling region, and approximately optimal setpoint based on data from at least one operating condition. The controller uses these setpoints initially to execute an optimal search to maximize performance by minimizing mechanical specific energy.

Buerger, Stephen↗

Control systems and methods to enable autonomous drilling

A system or method for drilling includes autonomously controlling a rotary or percussive drilling process as it transitions through multiple materials with very different dynamics. The method determines a drilling medium based on real-time measurements and comparison to prior drilling data, and identifies the material type, drilling region, and approximately optimal setpoint based on data from at least one operating condition. The controller uses these setpoints initially to execute an optimal search to maximize performance by minimizing mechanical specific energy. Near-bit depth-of-cut estimations are performed using a machine learning prediction deployed in an embedded processor to provide high-speed ROP estimates. The sensing capability is coupled with a near-bit clutching mechanism to support drilling dysfunction mitigation.

Buerger, Stephen↗

Control systems and methods to enable autonomous drilling

A system or method for drilling includes autonomously controlling a rotary or percussive drilling process as it transitions through multiple materials with very different dynamics. The method determines a drilling medium based on real-time measurements and comparison to prior drilling data, and identifies the material type, drilling region, and approximately optimal setpoint based on data from at least one operating condition. The controller uses these setpoints initially to execute an optimal search to maximize performance by minimizing mechanical specific energy. Near-bit depth-of-cut estimations are performed using a machine learning prediction deployed in an embedded processor to provide high-speed ROP estimates. The sensing capability is coupled with a near-bit clutching mechanism to support drilling dysfunction mitigation.

Buerger, Stephen↗

On the relationship between reliability and linear quadratic optimal control

The linear quadratic optimal control method is used today to solve many complex systems problems. As system complexity increases, and as linear quadratic optimal control is used in more demanding situations, the extension of the design methodology to cover system failures, robustness and reliability is of crucial importance. This paper documents the progress toward a theory which incorporates reliability in the performance index; a linear quadratic control problem is formulated which accounts for system effectiveness and gives an offline procedure for comparing two linear quadratic control systems on the basis of both reliability and performance.

Birdwell, J. D.↗

Stability and Performance Metrics for Adaptive Flight Control

This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.

Stepanyan, Vahram↗

Power control system modification and simulation of CPR1000 - 181

Due to development of electric power system, the proportion of nuclear power and its needs for load follow operation have become large. Then there would be higher requirements to the power control ability of the nuclear power system. The axial power distribution may change a lot in the operation process and be affected by many factors. In particular, as the power change is performed within a load follow maneuver, several modifications occur in the core from a neutronic view point: the fuel and moderator temperature change, the xenon concentration and distribution are modified, the power distribution skewed axially, etc. These changes need to be adequately counterbalanced to keep both the core critical and the power distribution acceptable. The traditional approach in pressurized water reactors (PWRs) is compensating for the reactivity change due to the power variation by adjusting the soluble boron concentration and moving a limited number of control banks. However, dilution/boronation strategy becomes expensive for short time changes and leads to large volume of liquid effluent, so it is eager about a capability to perform load follow operation without changing soluble boron concentration. CPR1000, one of the main reactor types in China national development, is taken an example in this paper. It adopts a control method called Mode G, using G banks, N banks, R bank and soluble boron to perform the load follow control. According to the analysis of the physics and thermal principle, a two-node dynamic function model was built, putting the coupling coefficient and mutual influence into consideration. By the calculation of these transient parameter values which are acquired by the steady-state calculation of single channel, the core system model of CPR1000 is established. In order to carry out the load follow operation without the boron adjustment, named as BTP mode, the control banks were regrouped to control the average temperature by M banks and axial offset by AO bank. After that, the average temperature control system (M banks control system) and the axial offset control system (AO bank control system) are built. When the optimal control system is connected to the core model simulation platform, the BTP mode load follow operation of the modified CPR1000 is simulated in the end of the paper. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A general weight matrix formulation using optimal control

Classical methods from optimal control theory are used in deriving general forms for neural network weights. The network learning or application task is encoded in a performance index of a general structure. Consequently, different instances of this performance index lead to special cases of weight rules, including some well-known forms. Comparisons are made with the outer product rule, spectral methods, and recurrent back-propagation. Simulation results and comparisons are presented.

Farotimi, Oluseyi↗

Application of Artificial Neural Network Model for Optimized Control of Condenser Water Temperature Set-Point in a Chilled Water System

Here, in this study, real-time predictive control and optimization model based on an ANN (artificial neural network) was developed to evaluate the cooling energy saving performance of the optimized control of CndWT (condenser water temperature). For this purpose, the difference in TCEC (total cooling energy consumption) between the conventional control strategy when the CndWT produced by the cooling tower is fixed and the optimized control strategy when real-time control of the CndWT through the optimal ANN model is applied was compared and analyzed. For the modeling of the building to be simulated, the co-simulation of EnergyPlus and MATLAB was built through the middleware Building Controls Virtual Test Bed. For the prediction of TCEC, an ANN model was developed through MATLAB's neural network toolbox. The model accuracy of the ANN was examined through Cv(RMSE) index and as a result, Cv(RMSE) of the optimized ANN model turned out to be approximately 25 %. More importantly, the predictive control technique was able to save TCEC by 5.6 % compared to the conventional control method constantly fixing CndWT set-point to 30 °C. These results showed that the CndWT needs to be dynamically controlled using artificial intelligence technique such as ANN model and that significant energy savings were achievable compared to the conventional fixed control.

42 ENGINEERING↗

Spacecraft drag-free technology development: On-board estimation and control synthesis

Estimation and control methods for a Drag-Free spacecraft are discussed. The functional and analytical synthesis of on-board estimators and controllers for an integrated attitude and translation control system is represented. The framework for detail definition and design of the baseline drag-free system is created. The techniques for solution of self-gravity and electrostatic charging problems are applicable generally, as is the control system development.

Key, R. W.↗

Advances in flow visualization using liquid-crystal coatings

This paper discusses a new four-part mixing method for visualizing boundary layer flows, including transitions, separation, and shock locations, by the use of liquid-crystal coatings. The method controls the event temperature and color-play bandwidth best suited to specific experimental conditions, and is easily learned. The method is applicable almost throughout the altitude and speed ranges for subsonic aircraft flight envelopes, and is also applicable to supersonic flow visualization and for general use in high- and low-speed wind tunnel and water tunnel testing.

Holmes, Bruce J.↗

Nonlinear Control of Large Disturbances in Magnetic Bearing Systems

In this paper, the nonlinear operation of magnetic bearing control methods is reviewed. For large disturbances, the effects of displacement constraints and power amplifier current and di/dt limits on bearing control system performance are analyzed. The operation of magnetic bearings exhibiting self-excited large scale oscillations have been studied both experimentally and by simulation. The simulation of the bearing system has been extended to include the effects of eddy currents in the actuators, so as to improve the accuracy of the simulation results. The results of these experiments and simulations are compared, and some useful conclusions are drawn for improving bearing system robustness.

Jiang, Yuhong↗

Distributed Reinforcement Learning with ADMM-RL

NREL researcher Peter Graf discusses distributed reinforcement learning with ADMM-RL as part of the Innovative Optimization and Control Methods for Highly Distributed Autonomous Systems workshop. NREL hosted the workshop to exchange ideas on state-of-the-art control and optimization strategies as well as get feedback on work being done at NREL.

97 MATHEMATICS AND COMPUTING↗

Toward Robustness Guarantees for Feedback-Based Optimization

NREL researcher Andrey Bernstein discusses the move toward robustness guarantees for feedback-based optimization as part of the Innovative Optimization and Control Methods for Highly Distributed Autonomous Systems workshop. NREL hosted the workshop to exchange ideas on state-of-the-art control and optimization strategies as well as get feedback on work being done at NREL.

24 POWER TRANSMISSION AND DISTRIBUTION↗