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A Privacy-Preserving Distributed Control of Optimal Power Flow
Here, we consider a distributed optimal power flow formulated as an optimization problem that maximizes a nondifferentiable concave function. Solving such a problem by the existing distributed algorithms can lead to data privacy issues because the solution information exchanged within the algorithms can be utilized by an adversary to infer the data. To preserve data privacy, in this paper we propose a differentially private projected subgradient (DP-PS) algorithm that includes a solution encryption step. We show that a sequence generated by DP-PS converges in expectation, in probability, and with probability 1. Moreover, we show that the rate of convergence in expectation is affected by a target privacy level of DP-PS chosen by the user. We conduct numerical experiments that demonstrate the convergence and data privacy preservation of DP-PS.
Optimization and Control of Burning Plasmas Through High Performance Computing
This project has revived the FACETS code, that has been developed under SciDAC fund- ing in 2008-2012. The code has been dormant for a number of years after the SciDAC funding stopped. FACETS depends on external packages. The external packages and libraries such as PETSc, FFTW, HDF5 and NETCDF that are included in FACETS have evolved during these years. Some packages in FACETS are also parts of other codes such as PlasmaState, NUBEAM, GACODES, and UEDGE. These packages have been also evolved together with their host codes which include TRANSP, TGYRO and XPTOR. Finally, there is also a set of packages in FACETS that are being developed and maintained by Tech-X. These packages include BILDER, SciMake, and FcioWrappers. Many of these packages evolved significantly during the last several years and FACETS had to be updated to synchronize with the re- cent progress in the external packages. The PI has introduced new changes to the BILDER package to support the updated interfaces to the external modules. During the last year of the project, the FACETS version of the UEDGE code has been extracted from FACETS as a standalone package. The PI collaborates with the scientists from LLNL on the updated UEDGE model in FACETS. Drs. T. Rognlien, M. Umansky and A. Dimits from LLNL are contributing to this task.
Hybrid Deep Reinforcement Learning For Online Distribution Power System Optimization and Control.
Abstract not provided.
Optimizing Layered Control Strategies for Reducing Exposure to SARS-CoV-2
While there is growing understanding of the predominance of the airborne mode of transmission of the SARS-CoV-2 virus, there is a lack of guidance on how to build an effective system of controls to mitigate transmission in enclosed spaces. Such a system integrates multiple hazard-specific control measures to both eliminate or replace a hazard, and safeguard individuals against potential exposure and infection. Controls are defined by the US Occupational Safety and Health Association (OSHA) as the use of engineering methods to reduce the level of hazard inside a confined space. The Hierarchy of Controls provides a framework through which a system of controls can be examined; identifying those which directly remove or replace a hazard as the most effective, and individual behavioral measures (e.g., masking or shielding) as least effective. Use of such a framework to quantify control effectiveness might allow for the promotion of spaces as meeting a certain threshold of safety, likely adding to the confidence of space users resulting in increases in various metrics such as sales, visits, or likes.
Analysis and Testing of Optimal Power Control Strategy for NASA Moon Base Interconnected DC Microgrid System
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Home energy management based on optimal production control scheduling with unknown regime switching
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Analysis and Testing of Optimal Power Control Strategy for NASA Moon Base Interconnected DC Microgrid System
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Sensitivity reduction using optimally derived controllers
Feedback structures to reduce parameter sensitivity of linear system derived from solution of classical linear regulator problem for design of automatic control systems
On the controllability of delay-differential systems.
Controllability type applicable to optimal control problems for systems described by delay differential equations
Optimization of stochastic processes - Midcourse guidance.
Filtering and optimal control problems for discrete stochastic dynamical systems, describing various feedback controls and midcourse guidance optimization
An optimized buffer controlled data compression system
The digital data compression system considered uses a buffer controlled aperture algorithm which minimizes the mean-squared error between the reconstructed receiver output and transmitter input. The data compression technique selected is based on the zero-order floating aperture prediction rule. It is assumed that the statistics of the input data are initially uniformly distributed, stationary, and first-order Markov. The problem is solved for stationary data. An approach is presented for extending the results to slowly varying uniformly distributed nonstationary Markov data.
Optimal selenodetic control
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Development of an optimal automatic control law and filter algorithm for steep glideslope capture and glideslope tracking
A digital automatic control law to capture a steep glideslope and track the glideslope to a specified altitude is developed for the longitudinal/vertical dynamics of a CTOL aircraft using modern estimation and control techniques. The control law uses a constant gain Kalman filter to process guidance information from the microwave landing system, and acceleration from body mounted accelerometer data. The filter outputs navigation data and wind velocity estimates which are used in controlling the aircraft. Results from a digital simulation of the aircraft dynamics and the control law are presented for various wind conditions.
Practical optimal flight control system design for helicopter aircraft. Volume 1: Technical Report
A method by which modern and classical theory techniques may be integrated in a synergistic fashion and used in the design of practical flight control systems is presented. A general procedure is developed, and several illustrative examples are included. Emphasis is placed not only on the synthesis of the design, but on the assessment of the results as well.
Automatic flare transition penetrating wind shears
In this paper, the development of a digital three-dimensional automatic control law designated to achieve an optimal transition of a large commercial aircraft between the glideslope conditions and the desired final touchdown condition is presented. The linearized equations representing the perturbed motion of the aircraft from the nominal glideslope trajectory are presented. A method of incorporating the spatial, low-level wind shears into these perturbed equations of motion is indicated. It is shown that the system equations then assume the familiar form of the linear regulator problem, acted upon by a constant disturbance. A design procedure is presented to compute a digital, time-invariant, optimal control law for the discrete regulator problem acted upon by a constant disturbance. The response trajectories presented demonstrate the capability of this controller to perform optimal flare maneuvers in the presence of various wind shear conditions.
A model for the submarine depthkeeping team
The most difficult task the depthkeeping team must face occurs during periscope-depth operations during which they may be required to maintain a submarine several hundred feet long within a foot of ordered depth and within one-half degree of ordered pitch. The difficulty is compounded by the facts that wave generated forces are extremely high, depth and pitch signals are very noisy and submarine speed is such that overall dynamics are slow. A mathematical simulation of the depthkeeping team based on the optimal control models is described. A solution of the optimal team control problem with an output control restriction (limited display to each controller) is presented.