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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Power-to-load balancing for asymmetric heave wave energy converters with nonideal power take-off

The aim of this study is to maximize the power-to-load ratio for asymmetric heave wave energy converters. Linear hydrodynamic theory was used to calculate bounds of the expected time-averaged power (TAP) and corresponding surge-restraining force, pitch-restraining torque, and power take-off (PTO) control force with the assumption of sinusoidal displacement. This paper formulates an optimal control problem to handle an objective function with competing terms in an attempt to maximize power capture while minimizing structural and actuator loads in regular and irregular waves. Penalty weights are placed on the surge-restraining force, pitch-restraining torque, and PTO actuation force, thereby allowing the control focus to concentrate on either power absorption or load mitigation. The penalty weights are used to control peak structural and actuator loads that were found to curb the additional losses in power absorption associated with a nonideal PTO. Thus, in achieving these goals, a per-unit gain in TAP would not lead to a greater per-unit demand in structural strength, hence yielding a favorable benefit-to-cost ratio. Demonstrative results for 'The Berkeley Wedge' in the form of output TAP, reactive TAP needed to drive WEC motion, and the amplitudes of the surge-restraining force, pitch-restraining torque, and PTO control force are shown.

16 TIDAL AND WAVE POWER↗
DOE OSTI2015

Optimal shielding design for minimum materials cost or mass

The mathematical underpinnings of cost optimal radiation shielding designs based on an extension of optimal control theory are presented, a heuristic algorithm to iteratively solve the resulting optimal design equations is suggested, and computational results for a simple test case are discussed. A typical radiation shielding design problem can have infinitely many solutions, all satisfying the problem's specified set of radiation attenuation requirements. Each such design has its own total materials cost. For a design to be optimal, no admissible change in its deployment of shielding materials can result in a lower cost. This applies in particular to very small changes, which can be restated using the calculus of variations as the Euler-Lagrange equations. Furthermore, the associated Hamiltonian function and application of Pontryagin's theorem lead to conditions for a shield to be optimal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1987

Optimal abort landing trajectories in the presence of windshear

The abort landing problem is considered with reference to flight in a vertical plane. It is assumed that, upon sensing that the aircraft is in a windshear, the pilot increases the power setting at a constant time rate until maximum power setting is reached; afterward, the power setting is held constant. The performance index being minimized is the peak value of the altitude drop; the resulting optimization problem is a minimax or Chebyshev problem of optimal control. It is found that, for strong-to-severe windshears, the optimal trajectory includes three branches: a descending flight branch followed by a nearly horizontal flight branch, followed by an ascending flight branch after the aircraft has passed through the shear region. The peak altitude drop depends on the windshear intensity, the initial altitude, and the power setting rate; it increases as the windshear intensity increases and the initial altitude increases, and it decreases as the power setting rate increases.

Miele, A.↗
NASA NTRS1989

Approximation in LQG control of a thermoelastic rod

Control and estimator gains are computed for linear-quadratic-Gaussian (LQG) optimal control of the axial vibrations of a thermoelastic rod. The computations are based on a modal approximation of the partial differential equations representing the rod, and convergence of the approximations to control and estimator gains is the main issue.

Gibson, J. S.↗
NASA NTRS1991

A new method of optimal design for a two-dimensional diffuser by using dynamic programming

A new method for predicting the optimal velocity distribution on the wall of a two dimensional diffuser is presented. The method uses dynamic programming to solve the optimal control problem with inequality constraints of state variables. The physical model of optimization is designed to prevent the separation of the boundary layer while approaching the maximum pressure ratio in a diffuser of a specified length. The computational results are in fair agreement with the experimental ones. Optimal velocity distribution on a diffuser wall is said to occur when the flow decelerates quickly at first and then smoothly, while the flow is near separation, but always protected from it. The optimal velocity distribution can be used to design the contour of the diffuser.

Gu, Chuangang↗
NASA NTRS2014

Active Vibration Control for Helicopter Interior Noise Reduction Using Power Minimization

This report describes work performed by United Technologies Research Center (UTRC) for NASA Langley Research Center (LaRC) under Contract NNL11AA06C. The objective of this program is to develop technology to reduce helicopter interior noise resulting from multiple gear meshing frequencies. A novel active vibration control approach called Minimum Actuation Power (MAP) is developed. MAP is an optimal control strategy that minimizes the total input power into a structure by monitoring and varying the input power of controlling sources. MAP control was implemented without explicit knowledge of the phasing and magnitude of the excitation sources by driving the real part of the input power from the controlling sources to zero. It is shown that this occurs when the total mechanical input power from the excitation and controlling sources is a minimum. MAP theory is developed for multiple excitation sources with arbitrary relative phasing for single or multiple discrete frequencies and controlled by a single or multiple controlling sources. Simulations and experimental results demonstrate the feasibility of MAP for structural vibration reduction of a realistic rotorcraft interior structure. MAP control resulted in significant average global vibration reduction of a single frequency and multiple frequency excitations with one controlling actuator. Simulations also demonstrate the potential effectiveness of the observed vibration reductions on interior radiated noise.

Mendoza, J.↗
DOE OSTI2016

Predictive Scheduling for Electric Vehicles Considering Uncertainty of Load and User Behaviors

Un-coordinated Electric Vehicle (EV) charging can create unexpected load in local distribution grid, which may degrade the power quality and system reliability. The uncertainty of EV load, user behaviors and other baseload in distribution grid, is one of challenges that impedes optimal control for EV charging problem. Previous researches did not fully solve this problem due to lack of real-world EV charging data and proper stochastic model to describe these behaviors. In this paper, we propose a new predictive EV scheduling algorithm (PESA) inspired by Model Predictive Control (MPC), which includes a dynamic load estimation module and a predictive optimization module. The user-related EV load and base load are dynamically estimated based on the historical data. At each time interval, the predictive optimization program will be computed for optimal schedules given the estimated parameters. Only the first element from the algorithm outputs will be implemented according to MPC paradigm. Current-multiplexing function in each Electric Vehicle Supply Equipment (EVSE) is considered and accordingly a virtual load is modeled to handle the uncertainties of future EV energy demands. This system is validated by the real-world EV charging data collected on UCLA campus and the experimental results indicate that our proposed model not only reduces load variation up to 40% but also maintains a high level of robustness. Finally, IEC 61850 standard is utilized to standardize the data models involved, which brings significance to more reliable and large-scale implementation.

Wang, Bin↗
NASA NTRS1987

Piecewise linear approximation for hereditary control problems

Finite dimensional approximations are presented for linear retarded functional differential equations by use of discontinuous piecewise linear functions. The approximation scheme is applied to optimal control problems when a quadratic cost integral has to be minimized subject to the controlled retarded system. It is shown that the approximate optimal feedback operators converge to the true ones both in case the cost integral ranges over a finite time interval as well as in the case it ranges over an infinite time interval. The arguments in the latter case rely on the fact that the piecewise linear approximations to stable systems are stable in a uniform sense. This feature is established using a vector-component stability criterion in the state space R(n) x L(2) and the favorable eigenvalue behavior of the piecewise linear approximations.

Propst, Georg↗
NASA NTRS1989

Active vibration control for flexible rotor by optimal direct-output feedback control

Experimental research tests were performed to actively control the rotor vibrations of a flexible rotor mounted on flexible bearing supports. The active control method used in the tests is called optimal direct-output feedback control. This method uses four electrodynamic actuators to apply control forces directly to the bearing housings in order to achieve effective vibration control of the rotor. The force actuators are controlled by an analog controller that accepts rotor displacement as input. The controller is programmed with experimentally determined feedback coefficients; the output is a control signal to the force actuators. The tests showed that this active control method reduced the rotor resonance peaks due to unbalance from approximately 250 micrometers down to approximately 25 micrometers (essentially runout level). The tests were conducted over a speed range from 0 to 10,000 rpm; the rotor system had nine critical speeds within this speed range. The method was effective in significantly reducing the rotor vibration for all of the vibration modes and critical speeds.

Nonami, Kenzou↗
NASA NTRS1989

Active vibration control for flexible rotor by optimal direct-output feedback control

Experimental research tests were performed to actively control the rotor vibrations of a flexible rotor mounted on flexible bearing supports. The active control method used in the tests is called optimal direct-output feedback control. This method uses four electrodynamic actuators to apply control forces directly to the bearing housings in order to achieve effective vibration control of the rotor. The force actuators are controlled by an analog controller that accepts rotor displacement as input. The controller is programmed with experimentally determined feedback coefficients; the output is a control signal to the force actuators. The tests showed that this active control method reduced the rotor resonance peaks due to unbalance from approximately 250 microns down to approximately 25 microns (essentially runout level). The tests were conducted over a speed range from 0 to 10,000 rpm; the rotor system had nine critical speeds within this speed range. The method was effective in significantly reducing the rotor vibration for all of the vibration modes and critical speeds.

Nonami, K.↗
NASA NTRS1992

Optimal motion planning for collision avoidance of mobile robots in non-stationary environments

An optimal control formulation of the problem of collision avoidance of mobile robots moving in general terrains containing moving obstacles is presented. A dynamic model of the mobile robot and the dynamic constraints are derived. Collision avoidance is guaranteed if the minimum distance between the robot and the object is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. Time consistency with the nominal plan is desirable. A numerical solution of the optimization problem is obtained. A perturbation control type of approach is used to update the optimal plan. Simulation results verify the value of the proposed strategy.

Kyriakopoulos, K. J.↗
DOE OSTI2023

Lower and upper threshold limit for artificial neural network based chilled and condenser water temperatures set-point control in a chilled water system

In this study, an ANN (artificial neural network) based real-time optimized control algorithm for a chilled water cooling system was developed and applied in an actual building to analyze its cooling energy saving effects through in-situ application and actual measurements. For this purpose, the cooling tower’s CndWT (condenser water temperature) and the chiller’s ChWT (chilled water temperature) were set as system control variables. To evaluate algorithm performance, the electric consumption and the COP (coefficient of performance) were compared and analyzed when ChWT and CndWTs were controlled conventionally and controlled based on the ANN. During the analysis, unexpected abnormal data was observed due to insufficient training data and limited consideration of OWBT (outdoor air wet-bulb temperature) when determining the CndWT set-point. Therefore, it is necessary to further build training data from a wider range of conditions and to set the lower limit of CndWT set-point to at least +3.6 °C above OWBT when the OWBT is higher than 23 °C, so that further energy savings can be achieved.

42 ENGINEERING↗
DOE OSTI2022

Harnessing deep reinforcement learning to construct time-dependent optimal fields for quantum control dynamics

Here, we present an efficient deep reinforcement learning (DRL) approach to automatically construct time-dependent optimal control fields that enable desired transitions in dynamical chemical systems. Our DRL approach gives impressive performance in constructing optimal control fields, even for cases that are difficult to converge with existing gradient-based approaches. We provide a detailed description of the algorithms and hyperparameters as well as performance metrics for our DRL-based approach. Our results demonstrate that DRL can be employed as an effective artificial intelligence approach to efficiently and autonomously design control fields in quantum dynamical chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Piecewise linear approximation for hereditary control problems

This paper presents finite-dimensional approximations for linear retarded functional differential equations by use of discontinuous piecewise linear functions. The approximation scheme is applied to optimal control problems, when a quadratic cost integral must be minimized subject to the controlled retarded system. It is shown that the approximate optimal feedback operators converge to the true ones both in the case where the cost integral ranges over a finite time interval, as well as in the case where it ranges over an infinite time interval. The arguments in the last case rely on the fact that the piecewise linear approximations to stable systems are stable in a uniform sense.

Propst, Georg↗
DOE OSTI2017

Building thermal model development of typical house in U.S. for virtual storage control of aggregated building loads based on limited available information

A building thermal model is an essential component for achieving optimal control of a building’s heating, ventilation, and air conditioning (HVAC). A self-learning grey-box model has been developed by implementing data-driven techniques and utilizing limited available information about the building. In previous research, detailed foreknown knowledge/information, e.g. physical and thermal properties of building materials, as well as sufficient number of observation points, e.g. indoor temperature sensors in different zones, are available for making the decision of model structure and parameters searching range easier. The availability of measured data and a narrowed searching range of model parameters, e.g. resistance and capacity for each wall, made the adopted algorithms quickly achieve near optimal values, which closely approximate the actual heat transfer of a building. Meanwhile, the details of pre-processing of the key inputs were seldom explained. Compared to the previous research, in this study, the available information is assumed to be limited which can fill the requirement for large scale virtual storage control of real residential community in near future, where it may be impractically or over time-consuming to acquire the detailed information for each single house. The developed model is validated by comparing the results to measured data in a recently-built home typical of the southeastern United States.

Cui, Borui↗
DOE OSTI2026

Toward real-time optimization through model reduction and model discrepancy sensitivities

Optimization problems arise in a range of scenarios, from optimal control to model parameter estimation. In many applications, such as the development of digital twins, it is essential to solve these optimization problems within wall-clock-time limitations. However, this is often unattainable for complex systems, such as those modeled by nonlinear partial differential equations. One strategy for mitigating this issue is to construct a reduced-order model (ROM) that enables more rapid optimization. In particular, the use of nonintrusive ROMs—those that do not require access to the full-order model at evaluation time—is popular because they facilitate the computation of optimization solutions within the wall-clock time requirements. However, the optimization solution will be unreliable if the iterates move outside the ROM training data. This article proposes the use of hyper-differential sensitivity analysis with respect to model discrepancy (HDSA-MD) as a computationally efficient tool to augment ROM-constrained optimization and improve its reliability. The proposed approach consists of two phases: (i) an offline phase where several full-order model evaluations are computed to train the ROM, and (ii) an online phase where a ROM-constrained optimization problem is solved, a limited number of full-order model evaluations are computed, and HDSA-MD is used to enhance the optimization solution. Numerical results are demonstrated for two examples, atmospheric contaminant control and wildfire ignition location estimation, in which a ROM is trained offline using inaccurate atmospheric data. In conclusion, the HDSA-MD update yields a significant improvement in the ROM-constrained optimization solution using only one full-order model evaluation online with corrected atmospheric data.

PDE-constrained optimization↗