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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Data-Enabled Predictive Control for Building HVAC Systems

Model predictive control is widely used as a control technology for the computation of optimal control inputs of building heating, ventilating, and air conditioning (HVAC) systems. However, both the benefits and widespread adoption of model predictive control (MPC) are hindered by the effort of model creation, calibration, and accuracy of the predictions. In this paper, we apply the data-enabled predictive control (DeePC) algorithm for designing controls for building HVAC systems. The algorithm solely depends on input/output data from the system to predict future state trajectories without the need for system identification. The algorithm relies on the idea that a vector space of all input–output trajectories of a discrete-time linear time-invariant (LTI) system is spanned by time-shifts of a single measured trajectory, given the input signal is persistently exciting. Closed-loop simulations using EnergyPlus are performed to demonstrate the approach. The simulated building modeled in EnergyPlus is a modified commercial large office prototype building served by an air handling unit-variable air volume HVAC system. Temperature setpoints of zones are used as control variables to minimize the HVAC energy cost of the building considering a time-of-use electricity rate structure. Furthermore, sensitivity analysis is conducted to gain insights into the effect of parameter tuning on DeePC performance. Simulation results are used to illustrate the performance of the algorithm and compare the algorithm with model-based MPC and occupancy-based setpoint controller. Overall, DeePC achieves similar performance compared to MPC for lower engineering effort.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1977

Prediction of pilot opinion ratings using an optimal pilot model

A brief review of some of the more pertinent applications of analytical pilot models to the prediction of aircraft handling qualities is undertaken. The relative ease with which multiloop piloting tasks can be modeled via the optimal control formulation makes the use of optimal pilot models particularly attractive for handling qualities research. To this end, a rating hypothesis is introduced which relates the numerical pilot opinion rating assigned to a particular vehicle and task to the numerical value of the index of performance resulting from an optimal pilot modeling procedure as applied to that vehicle and task. This hypothesis is tested using data from piloted simulations and is shown to be reasonable. An example concerning a helicopter landing approach is introduced to outline the predictive capability of the rating hypothesis in multiaxis piloting tasks.

Hess, R. A.↗
NASA NTRS1979

Algebraic methods for the solution of some linear matrix equations

The characterization of polynomials whose zeros lie in certain algebraic domains (and the unification of the ideas of Hermite and Lyapunov) is the basis for developing finite algorithms for the solution of linear matrix equations. Particular attention is given to equations PA + A'P = Q (the Lyapunov equation) and P - A'PA = Q the (discrete Lyapunov equation). The Lyapunov equation appears in several areas of control theory such as stability theory, optimal control (evaluation of quadratic integrals), stochastic control (evaluation of covariance matrices) and in the solution of the algebraic Riccati equation using Newton's method.

Djaferis, T. E.↗
NASA NTRS1982

Pilot model hypothesis testing

The aircraft control time history predicted by the optimal control pilot model and actual pilot tracking data obtained from NASA Langley's differential maneuvering simulator (DMS) are analyzed. The analysis is performed using a hypothesis testing scheme modified to allow for changes in the true hypothesis. A finite number of pilot models, each with different hypothesized internal model representations of the aircraft dynamics, are constructed. The hypothesis testing scheme determines the relative probability that each pilot model best matches the DMS data. By observing the changes in probabilities, it is possible to determine when the pilot changes control strategy and which hypothesized pilot model best represent's the pilot's control behavior.

Broussard, J. R.↗
NASA NTRS1983

Application of an adaptive blade control algorithm to a gust alleviation system

The feasibility of an adaptive control system designed to alleviate helicopter gust induced vibration was analytically investigated for an articulated rotor system. This control system is based on discrete optimal control theory, and is composed of a set of measurements (oscillatory hub forces and moments), an identification system using a Kalman filter, a control system based on the minimization of the quadratic performance function, and a simulation system of the helicopter rotor. The gust models are step and sinusoidal vertical gusts. Control inputs are selected at the gust frequency, subharmonic frequency, and superharmonic frequency, and are superimposed on the basic collective and cyclic control inputs. The response to be reduced is selected to be that at the gust frequency because this is the dominant response compared with sub- and superharmonics. Numerical calculations show that the adaptive blade pitch control algorithm satisfactorily alleviates the hub gust response. Almost 100% reduction of the perturbation thrust response to a step gust and more than 50% reduction to a sinusoidal gust are achieved in the numerical simulations.

Saito, S.↗
NASA NTRS1984

Application of an adaptive blade control algorithm to a gust alleviation system

The feasibility of an adaptive control system designed to alleviate helicopter gust induced vibration was analytically investigated for an articulated rotor system. This control system is based on discrete optimal control theory, and is composed of a set of measurements (oscillatory hub forces and moments), an identification system using a Kalman filter, a control system based on the minimization of the quadratic performance function, and a simulation system of the helicopter rotor. The gust models are step and sinusoidal vertical gusts. Control inputs are selected at the gust frequency, subharmonic frequency, and superharmonic frequency, and are superimposed on the basic collective and cyclic control inputs. The response to be reduced is selected to be that at the gust frequency because this is the dominant response compared with sub- and superharmonics. Numerical calculations show that the adaptive blade pitch control algorithm satisfactorily alleviates the hub gust response. Almost 100 percent reduction of the perturbation thrust response to a step gust and more than 50 percent reduction to a sinusoidal gust are achieved in the numerical simulations.

Saito, S.↗
NASA NTRS1983

Control of space stations

A study is made to develop controllers for the NASA-JSC Triangular Space Station and evaluate their performances to make recommendations for structural design and/or control alternatives. The control system design assumes the rigid body of the Space Station and developes the lumped parameter control system by using the Inverse Optimal Control Theory. In order to evaluate the performance of the control system, a Parameter Estimation algorithm is being developed which will be used in modeling an equivalent but simpler Space Station model. Finally, a scaled version of the Space Station is being built for the purpose of physical experiments to evaluate the control system performance.

Lee, K. Y.↗
NASA NTRS1988

Linear-Quadratic Controller For Aiming A Large Antenna

Independent control and estimator gains selected for optimal performance. Report describes use of techniques of linear-quadratic optimal control to design digital controller aiming large antenna. Based on closed-loop concept including mathematical model of plant and independently-selectable mathematical model estimates state of system.

Nickerson, Jackson A.↗
NASA NTRS1990

Estimability And Regulability Of Linear Systems

Report presents two new properties of systems characterized by linear state space models (e.g., dynamical systems and associated control systems): estimability and regulability. Provides criteria for reductions of errors and cost functions in control systems. Useful in design of optimal controllers and estimators.

Baram, Yoram↗
NASA NTRS1991

Neighboring extremal guidance for systems with a piecewise linear control

The neighboring extremal feedback control law is developed for systems with a piecewise linear control for the case where the optimal control is obtained by nonlinear programming techniques. To develop the control perturbation for a given deviation from the nominal path, the second variation is minimized subject to the constraint that the final conditions be satisfied. This process leads to a feedback relationship between the control perturbation and the measured deviation from the nominal state. A simple example, the lunar launch problem, is used to demonstrate the validity of the guidance law. For model errors on the order of 5 percent, the results indicate that 5 percent errors occur in the final conditions.

Hull, David G.↗
NASA NTRS1992

Neighboring suboptimal control

The neighboring extremal feedback control law is developed for systems with a piecewise linear control for the case where the optimal control is obtained by nonlinear programming techniques. To develop the control perturbation for a given deviation from the nominal path, the second variation is minimized subject to the constraint that the final conditions be satisfied. This process leads to a feedback relationship between the control perturbation and the measured deviation from the nominal state.

Hull, David G.↗
NASA NTRS1993

Feedback control for unsteady flow and its application to the stochastic Burgers equation

The study applies mathematical methods of control theory to the problem of control of fluid flow with the long-range objective of developing effective methods for the control of turbulent flows. Model problems are employed through the formalism and language of control theory to present the procedure of how to cast the problem of controlling turbulence into a problem in optimal control theory. Methods of calculus of variations through the adjoint state and gradient algorithms are used to present a suboptimal control and feedback procedure for stationary and time-dependent problems. Two types of controls are investigated: distributed and boundary controls. Several cases of both controls are numerically simulated to investigate the performances of the control algorithm. Most cases considered show significant reductions of the costs to be minimized. The dependence of the control algorithm on the time-descretization method is discussed.

Choi, Haecheon↗
NASA NTRS1996

Vibration Attenuation of the NASA Langley Evolutionary Structure Experiment Using H(infinity) and Structured Singular Value (mu) Robust Multivariable Control Techniques

This final report summarizes the research results under NASA Contract NAG-1-1254 from May, 1991 - April, 1995. The main contribution of this research are in the areas of control of flexible structures, model validation, optimal control analysis and synthesis techniques, and use of shape memory alloys for structural damping.

Balas, Gary J.↗
NASA NTRS2004

Frequency Weighted H2 Control Design for the Glovebox Integrated Microgravity Isolation Technology (g-LIMIT)

The acceleration environment on the International Space Station (ISS) exceeds the requirements of many microgravity experiments. The Glovebox Integrated Microgravity Isolation Technology (g-LIMIT) has been built by the NASA Marshall Space Flight Center to attenuate the nominal acceleration environment and provide some isolation for microgravity science experiments. The g-LIMIT uses Lorentz (voice-coil) magnetic actuators to isolate a platform, for mounting science payloads, from the nominal acceleration environment. The system utilizes payload-acceleration, relative-position, and relative-orientation measurements in a feedback controller to accomplish the vibration isolation task. The controller provides current commands to six magnetic actuators, producing the required experiment isolation from the ISS acceleration environment. The present work documents the development of a candidate control law to meet the acceleration attenuation requirements for the g-LIMIT experiment platform. The controller design is developed using linear optimal control techniques for frequency-weighted H2 norms. Comparison of performance and robustness to plant uncertainty for this control design approach is included in the discussion. System performance is demonstrated in the presence of plant modeling error.

Calhoun, Philip C.↗
NASA NTRS2017

Optimal Transport Based Control of Granular Imaging System in Space

"Orbiting Rainbows” is a paradigm for creating a space-based observatory (telescope) from confined and aligned granular media. The overall objective is to construct a very large and lightweight aperture in space using a cloud of micron-sized particles held in position and aligned by the application of external electromagnetic fields, thus alleviating the extreme expense of deploying and stabilizing large monolithic telescopes by reducing the mass of the primary aperture. Adaptive optics techniques for wavefront stabilization and computational imaging techniques are then used to remove the optical noise from the scattering reflections of the granular medium, and finally producing clean images within the diffraction limit. In this paper, we address one of the key challenges of this new paradigm, namely controlling the position and orientation of the granules or particles so that the cloud of particles achieves the desired shape of an ultra-lightweight telescope and points into the right orientation. A further complication arises due to the fact that the particles do not have any onboard actuators. A number of external electric-field-based actuators are used to control all the particles simultaneously. Moreover, the number of actuators are orders-of-magnitude smaller than the number of particles, making this system largely under-actuated. Since the cloud of particles in any plausible configuration can be modeled as a probability distribution over the workspace, we formulate this control challenge as an optimal transport problem and then show that our optimal transport based control law drives the cloud of particles from any initial distribution to the desired position distribution (optical surface) and angular distribution (polarization state). Simulation results demonstrate the effectiveness of our approach.

Bandyopadhyay, Saptarshi↗
NASA NTRS2020

Multi-Objective Flight Control for Ride Quality Improvement for Flexible Aircraft

This paper describes a multi-objective flight control system design for ride quality improvement for flexible aircraft using multi-functional distributed flight control surfaces. A multi-objective optimal control design is developed to provide an acceleration suppression capability in conjunction with a gust load alleviation in order to provide ride quality improvement. A gust estimation is developed to estimate the gust load using a recursive least-squares algorithm. A ride quality assessment study is conducted using a flexible wing generic transport model. Six different flight control designs are implemented. The study shows that ride quality can be significantly improved with the acceleration suppression control.

Nguyen, Nhan↗