Robust Parameter Estimation for Identifying Satellite Injection Orbits

Bock, Hans Georg; Kostina, Ekaterina; Schlöder, Johannes P.; Gienger, G.; Pallaschke, S.; Ziegler, Gerald

doi:10.1007/3-540-27170-8_3

Cited by 8 publications

(10 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The parameter estimation is carried out within the modeling environment gPROMS using the Maximum Likelihood method. To mitigate the risk of incurring into local minima, a multiple shooting technique was applied so that the optimization problem was solved with different guesses for the initial parameter values. The final values are reported in Table , coupled with the statistical analysis on the estimation.…”

Section: Model Calibrationmentioning

confidence: 99%

Model-Based Optimization of Microalgae Growth in a Batch Plant

Albarello

Simionato²,

Morosinotto

et al. 2019

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

The economic sustainability of microalgae-based processes is still a major issue hindering the industrial application of such technologies. In this work, a mathematical model describing microalgae in varying light and temperature conditions is used to propose an optimized operation policy to increase productivity. The model is calibrated experimentally to describe the growth of Scenedesmus sp. cultivated in two outdoor pilot photobioreactors with different volumes and then used to maximize algal biomass productivity by proposing a new harvesting policy of the culture. Experimental tests showed that a significant productivity increase is achievable using the optimized procedure. Simulated tests also highlighted that the additional implementation of an optimal temperature control strategy may lead to double biomass production.

show abstract

Section: Model Calibrationmentioning

confidence: 99%

Model-Based Optimization of Microalgae Growth in a Batch Plant

Albarello

Simionato²,

Morosinotto

et al. 2019

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

show abstract

“…Here, the underlying assumption is that the measurement errors have Gaussian probability distributions. This way (4) can be interpreted as a maximum likelihood parameter estimation problem [4], [29], recalling that the inverse variance matrices of the measurement errors, Σ k ∈ S 4 and W k,l ∈ S 3 , are assumed to be given.…”

Section: Maximum Likelihood State Estimationmentioning

confidence: 99%

“…where B R = diag(B i ) i∈R denotes the derivative of F while A R and C R denote the associated constraint Jacobian matrices, all evaluated a-posteriori at the optimal solution. A detailed derivation of this expression for the inverse Fisher information matrix in the context of constrained Gauss-Newton methods can be found in [4], see also [29]. The square-roots of selected diagonal elements of the above matrix relative to the nominal value of the associated parameter estimate can be found in Table I.…”

Section: A Posteriori Error Analysismentioning

confidence: 99%

“…we construct a variant of ALADIN based on generalized Gauss-Newton Hessian approximation. Such Gauss-Newton approximation based approaches have been analyzed exhaustively for unconstrained nonlinear least-squares problems [23,Chapter 10.3] as well as in the context of centralized parameter estimation of constrained problem as analyzed in [3], [4] and [24]. However, one interesting contribution of Section IV is analyzing such Hessian approximations in the context of distributed least squares estimation with the ALADIN framework proving a local convergence proof.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distributed State Estimation for AC Power Systems using Gauss-Newton ALADIN

Engelmann

Jiang

et al. 2019

2019 IEEE 58th Conference on Decision and Control (CDC)

View full text Add to dashboard Cite

This paper proposes a structure exploiting algorithm for solving non-convex power system state estimation problems in distributed fashion. Because the power flow equations in large electrical grid networks are non-convex equality constraints, we develop a tailored state estimator based on Augmented Lagrangian Alternating Direction Inexact Newton (ALADIN) method, which can handle the nonlinearities efficiently. Here, our focus is on using Gauss-Newton Hessian approximations within ALADIN in order to arrive at at an efficient (computationally and communicationally) variant of ALADIN for network maximum likelihood estimation problems. Analyzing an IEEE 30-Bus system we illustrate how the proposed algorithm can be used to solve highly nontrivial network state estimation problems. We also compare the method with existing distributed parameter estimation codes in order to illustrate its performance.2 Sometimes distributed approaches are also called hierarchical depending on the amount of central coordination [11].

show abstract

“…Die Verfahren wurden erfolgreich auf reale Probleme angewandt, u. a. zur Bahnbestimmung bei Satelliten [10] und katalytischer Enzymkonvertierung [8,11]. Die Verfahren wurden erfolgreich auf reale Probleme angewandt, u. a. zur Bahnbestimmung bei Satelliten [10] und katalytischer Enzymkonvertierung [8,11].…”

Section: Zusammenfassungunclassified

Robustheitsaspkete in der Parameterschätzung und optimale Versuchsplanung bei dynamischen Prozessen

Kostina¹

2006

Mitteilungen Der Deutschen Mathematiker-Vereinigung

View full text Add to dashboard Cite

Robust Parameter Estimation for Identifying Satellite Injection Orbits

Cited by 8 publications

References 5 publications

Model-Based Optimization of Microalgae Growth in a Batch Plant

Model-Based Optimization of Microalgae Growth in a Batch Plant

Distributed State Estimation for AC Power Systems using Gauss-Newton ALADIN

Robustheitsaspkete in der Parameterschätzung und optimale Versuchsplanung bei dynamischen Prozessen

Contact Info

Product

Resources

About