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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Snowmass 2021 Whitepaper: Proton Structure at the Precision Frontier

An overwhelming number of theoretical predictions for hadron colliders require parton distribution functions (PDFs), which are an important ingredient of theory infrastructure for the next generation of high-energy experiments. This whitepaper summarizes the status and future prospects for determination of high-precision PDFs applicable in a wide range of energies and experiments, in particular in precision tests of the Standard Model and in new physics searches at the high-luminosity Large Hadron Collider and Electron–Ion Collider. We discuss the envisioned advancements in experimental measurements, QCD theory, global analysis methodology, and computing that are necessary to bring unpolarized PDFs in the nucleon to the N2LO and N3LO accuracy in the QCD coupling strength. Special attention is given to the new tasks that emerge in the era of the precision PDF analysis, such as those focusing on the robust control of systematic factors both in experimental measurements and theoretical computations. Various synergies between experimental and theoretical studies of the hadron structure are explored, including opportunities for studying PDFs for nuclear and meson targets, PDFs with electroweak contributions or dependence on the transverse momentum, for incisive comparisons between phenomenological models for the PDFs and computations on discrete lattice, and for cross-fertilization with machine learning/AI approaches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1983

Design of a candidate flutter suppression control law for DAST ARW-2

A control law is developed to suppress symmetric flutter for a mathematical model of an aeroelastic research vehicle. An implementable control law is attained by including modified LQG (linear quadratic Gaussian) design techniques, controller order reduction, and gain scheduling. An alternate (complementary) design approach is illustrated for one flight condition wherein nongradient-based constrained optimization techniques are applied to maximize controller robustness.

Adams, W. M., Jr.↗
NASA NTRS1984

Design of a candidate flutter suppression control law for DAST ARW-2

A control law is developed to suppress symmetric flutter for a mathematical model of an aeroelastic research vehicle. An implementable control law is attained by including modified LQC (Linear Quadratic Gaussian) design techniques, controller order reduction, and gain scheduling. An alternate (complementary) design approach is illustrated for one flight condition wherein nongradient-based constrained optimization techniques are applied to maximize controller robustness.

Adams, W. M., Jr.↗
NASA NTRS1985

A research program in active control/aeroelasticity

In this research period a synthesis methodology for multifunctional robust aeroservoelastic systems was developed. The development consisted of the following stages: (1) development of an universal diagram to determine phase and gain margins of a multi-input multi-output (MIMO) system using singular value based stability margin criteria; (2) determination of singular value gradients with respect to design parameters and their application to improve stability margins of multiloop system; and (3) application of constrained optimization techniques to synthesize a low order robust controller for a high order MIMO aeroservoelastic system while satisfying several design constraints on the dynamic loads and responses and stability margins at the plant input and output. Overall research activities are summarized.

Source record↗
NASA NTRS1985

Development of a flutter suppression control law by use of linear quadratic Gaussian and constrained optimization design techniques

A control law to suppress symmetric flutter for a mathematical model of an aeroelastic research vehicle is developed. An implementable control law is attained by including modified linear quadratic Gaussian design techniques, controller order reduction, and gain scheduling. A complementary design approach for a flight condition wherein nongradient-based constrained optimization techniques are applied to maximize controller robustness is illustrated.

Adams, W. M.↗
NASA NTRS1985

Development of a flutter suppression control law by use of Linear Quadratic Gaussian and constrained optimization design techniques

A control law is developed to suppress symmetric flutter for a mathematical model of an aeroelastic research vehicle. An implementable control law is attained by including modified LQG (Linear Quadratic Gaussian) design techniques, controller order reduction, and gain scheduling. An alternate (complementary) design approach is illustrated for one flight condition wherein nongradient-based constrained optimization techniques are applied to maximize controller robustness.

Adams, W. M., Jr.↗
NASA NTRS1985

Robust detection, isolation, and accommodation for sensor failures

Recent advances in multivariable robust control system design are extended to sensor failure, detection, isolation, and accommodation (FDIA) and estimator design. A new concept called threshold selector is introduced. It represents a significant and innovative tool for the analysis and synthesis of FDIA algorithms. Analytical results are obtained for the SISO case to compute optimal thresholds and size of minimum detectable failures, and a computer-aided technique is developed for the multivariable case. The techniques have been applied to sensor FDIA for an aircraft turbine engine control system.

Emami-Naeini, A.↗
NASA NTRS1986

Hypothesis integration in image understanding systems

The goal of this research is to develop a robust control strategy for constructing image understanding systems (IUS). This paper proposes a general framework based on the integration of related hypotheses. Hypotheses are regarded as predictions of the occurrences of objects in the image. Related hypotheses are clustered together. A composite hypothesis is computed for each cluster. The goal of the IUS is to verify the hypotheses. We constructed an image understanding system, SIGMA, based on this framework and demonstrated its performance on an aerial image of a suburban housing development.

Hwang, Vincent Shang-Shouq↗
NASA NTRS1987

IECON '87: Industrial applications of control and simulation; Proceedings of the 1987 International Conference on Industrial Electronics, Control, and Instrumentation, Cambridge, MA, Nov. 3, 4, 1987

Recent advances in control-system design and simulation are discussed in reviews and reports. Among the topics considered are fast algorithms for generating near-optimal binary decision programs, trajectory control of robot manipulators with compensation of load effects via a six-axis force sensor, matrix integrators for real-time simulation, a high-level control language for an autonomous land vehicle, and a practical engineering design method for stable model-reference adaptive systems. Also addressed are the identification and control of flexible-limb robots with unknown loads, adaptive control and robust adaptive control for manipulators with feedforward compensation, adaptive pole-placement controllers with predictive action, variable-structure strategies for motion control, and digital signal-processor-based variable-structure controls.

Hartley, Tom T.↗
NASA NTRS1988

Effect of model uncertainty on failure detection - The threshold selector

The performance of all failure detection, isolation, and accomodation (DIA) algorithms is influenced by the presence of model uncertainty. A unique framework is presented to incorporate a knowledge of modeling error in the analysis and design of failure detection systems. The tools being used are very similar to those in robust control theory. A concept is introduced called the threshold selector, which is a nonlinear inequality whose solution defines the set of detectable sensor failure signals. The threshold selector represents an innovative tool for analysis and synthesis of DIA algorithms. It identifies the optimal threshold to be used in innovations-based DIA algorithms. The optimal threshold is shown to be a function of the bound on modeling errors, the noise properties, the speed of DIA filters, and the classes of reference and failure signals. The size of the smallest detectable failure is also determined. The results are applied to a multivariable turbofan jet engine example, which demonstrates improvements compared to previous studies.

Emami-Naeini, Abbas↗
NASA NTRS1989

Rarefied-flow aerodynamics measurement experiment on the aeroassist flight experiment

The rarefied-flow aerodynamics measurement experiment, which is expected to measure the rarefied-flow flight regime with an accelerometer on the aeroassist flight experiment, is discussed. The experiment concept and mission plans are examined and the experiment configuration is illustrated. The experiment plans include flight measurements of aerodynamic force and moment coefficients throughout the rarefied regime to verify ground-to-flight extrapolation techniques. In addition, the experiment includes the study of acceleration rates and the effects of attitude variation. The experiment is also expected to evaluate the determination of vehicle mass properties to study robust control theory formulations which are applicable to special return aeroassisted orbital transfer vehicle payloads.

Blanchard, R. C.↗
NASA NTRS1989

Experimental experience with flexible structures

The focus is on a flexible structure experiment developed at the California Institute of Technology. The main thrust of the experiment is to address the identification and robust control issues associated with large space structures by capturing their characteristics in the laboratory. The design, modeling, identification and control objectives will be discussed. Also, the subject of uncertainty in structural plant models and the frequency shaping of performance objectives will be expounded upon. Theoretical and experimental results of control laws designed using the identified model and uncertainty descriptions will be presented.

Balas, Gary J.↗
NASA NTRS1992

Automated Characterization Of Vibrations Of A Structure

Automated method of characterizing dynamical properties of large flexible structure yields estimates of modal parameters used by robust control system to stabilize structure and minimize undesired motions. Based on extraction of desired modal and control-design data from responses of structure to known vibrational excitations. Applicable to terrestrial structures where vibrations are important - aircraft, buildings, bridges, cranes, and drill strings.

Bayard, David S.↗
NASA NTRS1991

A linear programming approach to characterizing norm bounded uncertainty from experimental data

The linear programming spectral overbounding and factorization (LPSOF) algorithm, an algorithm for finding a minimum phase transfer function of specified order whose magnitude tightly overbounds a specified nonparametric function of frequency, is introduced. This method has direct application to transforming nonparametric uncertainty bounds (available from system identification experiments) into parametric representations required for modern robust control design software (i.e., a minimum-phase transfer function multiplied by a norm-bounded perturbation).

Scheid, R. E.↗
NASA NTRS1993

Robust stability of second-order systems

A feedback linearization technique is used in conjunction with passivity concepts to design robust controllers for space robots. It is assumed that bounded modeling uncertainties exist in the inertia matrix and the vector representing the coriolis, centripetal, and friction forces. Under these assumptions, the controller guarantees asymptotic tracking of the joint variables. A Lagrangian approach is used to develop a dynamic model for space robots. Closed-loop simulation results are illustrated for a simple case of a single link planar manipulator with freely floating base.

Chuang, C.-H.↗
NASA NTRS1993

Quantification of model error via an interval model with nonparametric error bound

The quantification of model uncertainty is becoming increasingly important as robust control is an important tool for control system design and analysis. This paper presents an algorithm that effectively characterizes the model uncertainty in terms of parametric and nonparametric uncertainties. The algorithm utilizes the frequency domain model error which is estimated from the spectra of output error and input data. The parametric uncertainty is represented as an interval transfer function while the nonparametric uncertainty is bounded by a designed error bound transfer function. Both discrete and continuous systems are discussed in this paper. The algorithm is applied to the Mini-Mast example, and the detail analysis is given.

Lew, Jiann-Shiun↗
NASA NTRS1994

Robust stability of second-order systems

This progress report gives current progress of the research in nonlinear robust control using positive real concept. The progress is documented in a draft paper. In the paper, the manipulator dynamics is reformulated differently from the existing equations of motion for free base robots. This new formulation gives a compact form of the dynamic equations for easy computation. The nonlinear terms are now considered. The results show that for an additional nonlinear friction term, the feedback controller designed using passivity concept works quite well. Although design of such a controller requires simulation of the dynamics for the example shown in the following draft, this design procedure is feasible.

Chuang, C.-H.↗
NASA NTRS1998

On the Numerical Formulation of Parametric Linear Fractional Transformation (LFT) Uncertainty Models for Multivariate Matrix Polynomial Problems

Robust control system analysis and design is based on an uncertainty description, called a linear fractional transformation (LFT), which separates the uncertain (or varying) part of the system from the nominal system. These models are also useful in the design of gain-scheduled control systems based on Linear Parameter Varying (LPV) methods. Low-order LFT models are difficult to form for problems involving nonlinear parameter variations. This paper presents a numerical computational method for constructing and LFT model for a given LPV model. The method is developed for multivariate polynomial problems, and uses simple matrix computations to obtain an exact low-order LFT representation of the given LPV system without the use of model reduction. Although the method is developed for multivariate polynomial problems, multivariate rational problems can also be solved using this method by reformulating the rational problem into a polynomial form.

Belcastro, Christine M.↗