Perturbation analysis of a maximum-likelihood objective function

Hsueh, A.; Mendel, Jerry M.

doi:10.1109/tac.1983.1103188

Cited by 2 publications

(3 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the regression of the binary VLE data, the maximum likelihood objective function was used where σ is the standard deviation of the measured variables.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Isobaric Vapor–Liquid Equilibrium Data for the Acetone + Hexamethyl Disiloxane + Ethyl Acetate Ternary System at 101.3 kPa: Determination and Correlation

Gong

2018

J. Chem. Eng. Data

View full text Add to dashboard Cite

Vapor−liquid equilibrium (VLE) data for the binary system of acetone (1) + hexamethyl disiloxane (HMDSO, 2) and the ternary system of acetone (1) + HMDSO (2) + ethyl acetate (EAC, 3) were obtained at 101.3 kPa. The acetone (1) + HMDSO (2) mixture had azeotropic temperature of 329.00 K, x 1,az = 0.9661. The binary VLE values and ternary VLE values were confirmed to be thermodynamically consistent using the Herington method and the McDermott−Ellis method, respectively. The binary VLE data were correlated using the nonrandom two-liquid (NRTL), universal quasichemical activity coefficient (UNIQUAC), and Wilson models, and the NRTL model has the best correlation with the experimental data. Furthermore, the acetone (1) + HMDSO (2) + EAC (3) ternary VLE data were predicted with the NRTL model using the binary interaction parameter obtained by association of the contained binary system, and the calculated data were in good agreement with the ternary experimental data. To further describe the ternary system, the residue curves were provided by Aspen Plus using the NRTL model.

show abstract

“…In the regression of the binary VLE data, the maximum likelihood objective function was used where σ is the standard deviation of the measured variables.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, the NRTL model could make a good prediction of the VLE data of the ternary system. The maximum likelihood objective function for the regression of the ternary VLE data was: 22…”

Section: Resultsmentioning

confidence: 99%

Isobaric Vapor–Liquid Equilibrium Data for the Acetone + Hexamethyl Disiloxane + Ethyl Acetate Ternary System at 101.3 kPa: Determination and Correlation

Gong

2018

J. Chem. Eng. Data

View full text Add to dashboard Cite

show abstract

“…We next show the optimality of the ML objective function with respect to a * pq more explicitly to establish how the measurements from the optimal pseudopoint indeed yield the best ML estimate for . We recall from [35] that the maximization problem for ML estimation, i.e., the first substep of step 7 in Algorithm 1, can be written equivalently as…”

Section: A Perturbation Analysis Of ML Objectivementioning

confidence: 99%

Optimal Measurement Allocation Algorithms for Parametric Model Identification of Power Systems

Chakrabortty

Martin

2014

IEEE Trans. Contr. Syst. Technol.

View full text Add to dashboard Cite

In this paper, we present an optimization algorithm that selects the optimal sets of points for placing phasor measurement units (PMUs) on the transmission lines of a multimachine power system for the purpose of identifying the best model fit for its wide-area swing dynamics. Alternatively, the method can also be viewed as a way to select the optimal set of points at which phasor values should be computed using measurements available from PMUs such that these computed values, also referred to here as pseudo-measurements, can generate the best estimate of the swing model, especially when the measurements are noisy. We pose the identification problem as an equivalent parameter estimation problem for the admittance of each tieline and the inertia of each machine using phasor measurements of voltage magnitude, phase angle and frequency, corrupted with high-frequency measurement noise. We then formulate the Cramer-Rao bounds (CRBs) for the estimates of these unknown parameters, and show that the bounds are functions of the PMU locations and of the contribution of each measurement variable in the combined output. We finally state the condition for finding the optimal PMU location that guarantees the tightest CRB, and, therefore, the most accurate swing model for the system.Index Terms-Cramer-Rao bound (CRB), parameter estimation, phasor measurment unit (PMU) allocation, pseudomeasurements, swing dynamics.

show abstract

Perturbation analysis of a maximum-likelihood objective function

Cited by 2 publications

References 1 publication

Isobaric Vapor–Liquid Equilibrium Data for the Acetone + Hexamethyl Disiloxane + Ethyl Acetate Ternary System at 101.3 kPa: Determination and Correlation

Isobaric Vapor–Liquid Equilibrium Data for the Acetone + Hexamethyl Disiloxane + Ethyl Acetate Ternary System at 101.3 kPa: Determination and Correlation

Optimal Measurement Allocation Algorithms for Parametric Model Identification of Power Systems

Contact Info

Product

Resources

About