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At least 469 records · Page 26

Development of control quality factor for HVAC control loop performance assessment I—Methodology (ASHRAE RP-1587)

This article is the second paper from the ASHRAE research project RP-1587, focusing on the methodology of obtaining a control quality factor (CQF). This article presents a development of two CQFs for assessing the heating, ventilation, and air-conditioning (HVAC) control loop performance. Both CQFs are able to detect whether the control loop is able to maintain the setpoint and identify the loop's ability to handle disturbances. In addition, the reversal behaviors are assessed as well. The first CQF (CQF-Harris) is proposed based on the normalized Harris index using the recursive least squares method. This recursive least squares method is selected because of its computational efficiency compared with the maximum likelihood estimation method. The second CQF (CQF-EWMA) is based on the exponentially weighted moving average of the error ratio. The assessment scale of excellent, good, fair, bad, and failed, which indicates the quality of the HVAC control loops, is established as well. The sensitivity analysis for both CQFs is also conducted, and it provides insights on choosing the appropriate parameters to compute such CQFs. Such parameters include the sampling frequency, the length of the moving window, and the variance of the unmeasured disturbance. The field evaluations and tests of the proposed CQFs for simulated control loops and real control loops can be found in the companion paper with the title 'Development of Control Quality Factor for HVAC Control Loop Performance Assessment - III: Field Testing and Results (ASHRAE RP-1587).'

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Evaluation of Piloted Inputs for Onboard Frequency Response Estimation

Frequency response estimation results are presented using piloted inputs and a real-time estimation method recently developed for multisine inputs. A nonlinear simulation of the F-16 and a Piper Saratoga research aircraft were subjected to different piloted test inputs while the short period stabilator/elevator to pitch rate frequency response was estimated. Results show that the method can produce accurate results using wide-band piloted inputs instead of multisines. A new metric is introduced for evaluating which data points to include in the analysis and recommendations are provided for applying this method with piloted inputs.

Grauer, Jared A.↗

A decision directed detector for the phase incoherent Gaussian channel

A vector digital signalling scheme is proposed for simultaneous adaptive data transmission and phase estimation. The use of maximum likelihood estimation methods predicts a better performance than the phase-locked loop. The phase estimate is shown to converge to the true value, so that the adaptive nature of the detector effectively achieves phase acquisition and improvement in performance. No separate synchronization interval is required and phase fluctuations can be tracked simultaneously with the transmission of information.

Kazakos, D.↗

Evaluation of large area crop estimation techniques

The performance of the USDAs EDITOR system is evaluated. The system processes Landsat imagery and estimates crop hectarage for large areas based on a regression estimator developed on a sample with known ground truth. It is found that use of multitemporal data over unitemporal significantly improves the hectarage estimates, and a 15% reduction in the r-squared of the regression occurs when independent and jackknifed test sets are used to evaluate the performance of the estimator. When an alternative clustering algorithm, CLASSY, is substituted for the current EDITOR method, estimator performance is improved with reduced need for analyst decisions. It is recommended that the CLASSY clustering algorithm and some form of jackknifing be implemented on EDITOR.

Amis, M. L.↗

Determination of aerodynamic parameters of a fighter airplane from flight data at high angles of attack

A procedure for the estimation of airplane model structure and parameters is applied to data from a modern fighter airplane operating within an angle of attack range of 5 to 60 deg. The paper briefly describes the airplane, flight and wind tunnel data available, and the estimation method. The results presented contain basic longitudinal characteristics of the airplane and the estimates of aerodynamic parameters in the yawing-moment equations. These estimates are obtained from small and large amplitude maneuvers. Because the latter set of data was not suitable for airplane identification, some of the large amplitude maneuvers were joined together and then partitioned into subsets according to the values of angle of attack. Each subset was then analyzed as a separate data set. Most of the estimated parameters and functions are in good agreement with the wind tunnel measurements. The estimated lateral parameters in the model equations also demonstrate good prediction capabilities.

Klein, V.↗

Readings in program control

Under the heading of Program Control, a number of related topics are discussed: cost estimating methods; planning and scheduling; cost overruns in the defense industry; the history of estimating; the advantages of cost plus award fee contracts; and how program control techniques led to the success of a NASA development project.

Hoban, Francis T.↗

Optimal Design of Calibration Signals in Space Borne Gravitational Wave Detectors

Future space borne gravitational wave detectors will require a precise definition of calibration signals to ensure the achievement of their design sensitivity. The careful design of the test signals plays a key role in the correct understanding and characterization of these instruments. In that sense, methods achieving optimal experiment designs must be considered as complementary to the parameter estimation methods being used to determine the parameters describing the system. The relevance of experiment design is particularly significant for the LISA Pathfinder mission, which will spend most of its operation time performing experiments to characterize key technologies for future space borne gravitational wave observatories. Here we propose a framework to derive the optimal signals in terms of minimum parameter uncertainty to be injected to these instruments during its calibration phase. We compare our results with an alternative numerical algorithm which achieves an optimal input signal by iteratively improving an initial guess. We show agreement of both approaches when applied to the LISA Pathfinder case.

LISA Path_nder mission↗

Online Static Load Model Estimation in Distribution Systems

This paper focuses on parameter identification for time-varying voltage-dependent polynomial load models in distribution systems—namely, the constant impedance (Z), constant current (I), and constant power (P). The paper assumes the presence of measurements at the distribution nodes from various sources, each at varying temporal resolutions. The least- squares estimation method with bounded variables is used to convert the measurements into ZIP parameter estimations for loads at various locations on the feeder. The results and discussions focus on some of the estimation issues faced in a distribution system caused by varying voltage sensitivities of loads along a feeder, measurement resolution, impact of window size and sampling rate of measurement data. Finally, the paper uses dynamic simulations data (synthetic high-resolution measurements) to further improve the estimation results.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Foundations for estimation by the method of least squares

Least squares estimation is discussed from the point of view of a statistician. Much of the emphasis is on problems encountered in application and, more specifically, on questions involving assumptions: what assumptions are needed, when are they needed, what happens if they are not valid, and if they are invalid, how that fact can be detected.

Hauck, W. W., Jr.↗

Effects of flight instrumentation errors on the estimation of aircraft stability and control derivatives

An error analysis program based on an output error estimation method was used to evaluate the effects of sensor and instrumentation errors on the estimation of aircraft stability and control derivatives. A Monte Carlo analysis was performed using simulated flight data for a high performance military aircraft, a large commercial transport, and a small general aviation aircraft for typical cruise flight conditions. The effects of varying the input sequence and combinations of the sensor and instrumentation errors were investigated. The results indicate that both the parameter accuracy and the corresponding measurement trajectory fit error can be significantly affected. Of the error sources considered, instrumentation lags and control measurement errors were found to be most significant.

Bryant, W. H.↗

Application of the Two-Step Filter to Process Ranging Measurements for Relative Navigation in an Elliptical Orbit

This estimator breaks a nonlinear estimation problem into a set of over determined 'first step' states which are linear in the observations and 'second step' states which are ultimately the states of interest. Linear estimation methods are applied to filter the observations and produce the optimal first step state estimate. The 'second step' states are obtained through iterative nonlinear parameter estimation considering the first step states as observations. It has been shown that this process exactly minimizes the least squares cost function for static problems and provides a better solution than the iterated extended Kalman filter (EKF) for dynamic problems. The two step filter is applied in this paper to process range and range rate measurements between the two spacecraft. Details of the application of the two step estimator to this problem will be given, highlighting the use of a test for ill-conditioned covariance estimates that can result from the first order covariance propagation. A comparison will be made between the performance of the two step filter and the IEKF.

Garrison, James L.↗

Physics-Informed Deep Neural Network Method for Limited Observability State Estimation

The precise knowledge regarding the state of the power grid is important in order to ensure optimal and reliable grid operation. Specifically, knowing the state of the distribution grid becomes increasingly important as more renewable energy sources are connected directly into the distribution network, increasing the fluctuations of the injected power. In this paper, we consider the case when the distribution grid becomes partially observable, due to for example cyber attacks, and the state estimation problem is under-determined. We present a new methodology that leverages a deep neural network (DNN) to estimate the grid state. The standard DNN training method is modified to explicitly incorporate the physical information of the grid topology and line/shunt admittance. We show that our method leads to a superior accuracy of the estimation when compared to the case when no physical information is provided. Finally, we compare the performance of our method to the standard state estimation approach, which is based on the weighted least squares with pseudo-measurements, and show that our method performs significantly better with respect to the estimation accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Error Bounds for Dynamical Spectral Estimation

Dynamical spectral estimation is a well-established numerical approach for estimating eigenvalues and eigenfunctions of the Markov transition operator from trajectory data. Although the approach has been widely applied in biomolecular simulations, its error properties remain poorly understood. Here we analyze the error of a dynamical spectral estimation method called “the variational approach to conformational dynamics" (VAC). We bound the approximation error and estimation error for VAC estimates. Our analysis establishes VAC's convergence properties and suggests new strategies for tuning VAC to improve accuracy.

97 MATHEMATICS AND COMPUTING↗

Spread Spectrum Symbol Detection With Blind Interference Suppression in FBMC-SS

Recent works have demonstrated Filter Bank Multicarrier Spread Spectrum (FBMC-SS) to be a robust communication scheme in the presence of high-power interferers. Existing FBMC-SS symbol detector designs based on analysis filter banks (AFB) suggest using an optimal combining scheme to suppress the interferers, necessitating some noise/interference power estimation method. In this paper, we introduce a symbol detector with blind interference suppression by extending a recently developed packet detection method. We then provide an analysis to show that the existing AFB-based symbol detector and the one proposed in this paper are equivalent in typical usage scenarios. A fully-fledged receiver design is proposed utilizing this symbol detector, with specifics presented for estimation of the channel impulse response and carrier frequency offset (CFO). We also outline a method of iterating upon the channel and CFO estimations to improve the quality of both parameters. Moreover, a modification to allow improved performance of the symbol detector at high SNR is provided. Finally, simulated performance results are presented to corroborate these findings and demonstrate the efficiency of this receiver design.

99 GENERAL AND MISCELLANEOUS↗

Top-of-atmosphere radiative fluxes - Validation of ERBE scanner inversion algorithm using Nimbus-7 ERB data

The ERBE algorithm is applied to the Nimbus-7 earth radiation budget (ERB) scanner data for June 1979 to analyze the performance of an inversion method in deriving top-of-atmosphere albedos and longwave radiative fluxes. The performance is assessed by comparing ERBE algorithm results with appropriate results derived using the sorting-by-angular-bins (SAB) method, the ERB MATRIX algorithm, and the 'new-cloud ERB' (NCLE) algorithm. Comparisons are made for top-of-atmosphere albedos, longwave fluxes, viewing zenith-angle dependence of derived albedos and longwave fluxes, and cloud fractional coverage. Using the SAB method as a reference, the rms accuracy of monthly average ERBE-derived results are estimated to be 0.0165 (5.6 W/sq m) for albedos (shortwave fluxes) and 3.0 W/sq m for longwave fluxes. The ERBE-derived results were found to depend systematically on the viewing zenith angle, varying from near nadir to near the limb by about 10 percent for albedos and by 6-7 percent for longwave fluxes. Analyses indicated that the ERBE angular models are the most likely source of the systematic angular dependences. Comparison of the ERBE-derived cloud fractions, based on a maximum-likelihood estimation method, with results from the NCLE showed agreement within about 10 percent.

Suttles, John T.↗

Representation of Probability Density Functions from Orbit Determination using the Particle Filter

Statistical orbit determination enables us to obtain estimates of the state and the statistical information of its region of uncertainty. In order to obtain an accurate representation of the probability density function (PDF) that incorporates higher order statistical information, we propose the use of nonlinear estimation methods such as the Particle Filter. The Particle Filter (PF) is capable of providing a PDF representation of the state estimates whose accuracy is dependent on the number of particles or samples used. For this method to be applicable to real case scenarios, we need a way of accurately representing the PDF in a compressed manner with little information loss. Hence we propose using the Independent Component Analysis (ICA) as a non-Gaussian dimensional reduction method that is capable of maintaining higher order statistical information obtained using the PF. Methods such as the Principal Component Analysis (PCA) are based on utilizing up to second order statistics, hence will not suffice in maintaining maximum information content. Both the PCA and the ICA are applied to two scenarios that involve a highly eccentric orbit with a lower apriori uncertainty covariance and a less eccentric orbit with a higher a priori uncertainty covariance, to illustrate the capability of the ICA in relation to the PCA.

Mashiku, Alinda K.↗

Nonlinear Dynamic Control Derivative Analysis for Aircraft with Application to Transonic Truss-Braced Wing

This paper presents the development of a nonlinear dynamic control derivative estimation method. A nonlinear aerodynamic model is developed to account for the effects of large control surface deflections on aircraft aerodynamic forces and moments. A series of unsteady RANS CFD simulations is performed to simulate the control surface oscillations at various reduced frequencies. The time-domain data are transformed into the frequency-domain data by a Fourier series analysis. Transfer functions of the dynamic control derivatives are then estimated by a frequency-domain regression. The method is applied to the Transonic Truss-Braced Wing (TTBW) to estimate the dynamic control derivatives for the elevator, aileron, and rudder.

Aircraft Control Derivatives↗

Caribbean deepwater snappers: Application of the bomb radiocarbon age estimation validation in understanding aspects of ecology and life history

Reef fishes have been utilized as food fish throughout the U.S. Caribbean and Gulf of Mexico waters for centuries, with increasing fishing effort in recent decades. As a result, many species have experienced declines in landings, including deepwater snappers such as queen snapper Etelis oculatus and blackfin snapper Lutjanus buccanella . However, little to no peer-reviewed published research exists on basic life history parameters for either species. Confirming the accuracy of an age estimation method for a fish species is essential for ensuring sustainable fisheries management. This is because in the assessment of fisheries species population age-based parameters, including longevity, age at sexual maturity, growth rate, mortality, age-specific reproductive output, and lifetime reproductive output, are important in understanding overall life history strategies of managed stocks. The past stock assessment on U.S. Caribbean queen snapper utilized an estimated longevity of 8 y, derived from length frequencies for fish from St. Lucia. Blackfin snapper has an estimated longevity of 27 y based on a relatively small study from offshore waters of the southeastern U.S. The focus of our investigation was to estimate maximum longevity of two data-poor species in the U.S. Caribbean. The accuracy of ageing methods was tested via bomb radiocarbon age estimation validation and effects of depth on Δ 14 C in otolith cores and eye lens core values were examined. Results from our work indicate a maximum validated age of 45 y for queen snapper, and 43 y for blackfin snapper. Our findings indicate queen snapper and blackfin snapper are long-lived (> 40 y). The resulting Δ 14 C comparison between eye lens cores and otolith cores has important implications for the study of age validation, specifically when deepwater species are involved.

59 BASIC BIOLOGICAL SCIENCES↗