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At least 109 records · Page 6

A large-scale benchmarking of deterministic and stochastic derivative-free optimization algorithms

This presentation summarizes our work in the PrOMMiS project on benchmarking of data-driven optimization algorithms and their applications in self-driving laboratories. This work supports the broader project goal of accelerating the identification of promising separation methods and operating conditions for critical minerals separation processes. We present a systematic benchmarking study of 42 data-driven optimization algorithms on a broad collection of 502 test problems. The results identify BAM, GLCCLUSTER, and MULTIMIN as the most effective optimization solvers, with BAM showing the highest overall performance and solving more than 80% of the benchmark problems. The study also shows that no single solver consistently outperforms the others across all problem types, indicating that our future laboratory applications may benefit from using a small set of strong solvers rather than relying on a single method. The presentation also illustrates an in-silico chemical reactor case study showing that data-driven optimization methods can guide autonomous experimentation in a self-driving laboratory and identify optimal operating conditions within a small number of experiments. Overall, the results provide a basis for selecting efficient optimization methods and demonstrate the practical use of data-driven optimization in self-driving laboratory workflows.

36 MATERIALS SCIENCE

Parameter estimation in linear models of the human operator in a closed loop with application of deterministic test signals

Parameter estimation techniques are discussed with emphasis on unbiased estimates in the presence of noise. A distinction between open and closed loop systems is made. A method is given based on the application of external forcing functions consisting of a sun of sinusoids; this method is thus based on the estimation of Fourier coefficients and is applicable for models with poles and zeros in open and closed loop systems.

Vanlunteren, A.

Deterministic optimal maneuver strategy for multi-target missions

This paper presents an optimal strategy for making impulsive correction to a multi-target trajectory by a single maneuver. The concept of an optimal maneuver time is introduced. The choice of suitable weighting functions is explored to enable one to properly translate the subjective desire of mission success into an objective cost function whose minimization yields the optimal strategy. It is shown that a number of strategies previously formulated are derivable from one general expression. A number of other interesting properties of the optimal strategy are described. Numerical results are presented for a typical two-target mission. It is shown that the strategy formulated is optimal. For some perturbations, there exists an optimal maneuver time different from the time of initiation of the perturbation. That is, the physical properties of the trajectory can be exploited to select the optimal time of making a corrective maneuver.

Dwivedi, N. P.

Probabilistic and deterministic aspects of linear estimation in geodesy

Recent advances in observational techniques related to geodetic work (VLBI, laser ranging) make it imperative that more consideration should be given to modeling problems. Uncertainties in the effect of atmospheric refraction, polar motion and precession-nutation parameters, cannot be dispensed with in the context of centimeter level geodesy. Even physical processes that have generally been previously altogether neglected (station motions) must now be taken into consideration. The problem of modeling functions of time or space, or at least their values at observation points (epochs) is explored. When the nature of the function to be modeled is unknown. The need to include a limited number of terms and to a priori decide upon a specific form may result in a representation which fails to sufficiently approximate the unknown function. An alternative approach of increasing application is the modeling of unknown functions as stochastic processes.

Dermanis, A.

Alleviation of helicopter fuselage-induced rotor unsteady loads through deterministic variation of the individual blade pitch

The effect of fuselage-induced upwash on the flapwise motion of a hinged rotor blade is considered. The typical upwash field is simulated through the flow produced by a moving point source. The resulting blade response is then approximated by its rigid flapping and first bending mode. The perturbation blade pitch variation required to alleviate its response to the upwash in the sense of either reducing the increased hub shear or minimization of the blade overall time averaged deflection, is determined. Calculations are carried out for a model rotor and for the case with increased Lock number. The results are presented in graph form. It is found that the minimum blade deflection criteria suppress the rigid flapping by a large amount and reduce the peak-to-peak value of the blade hub shear by at least 50 percent without causing an additional increase in blade stresses.

Rahnema, M. A.

Some critical questions about deterministic and stochastic adaptive control algorithms

The purpose of this informal paper is to discuss certain robustness issues associated with existing adaptive control algorithms. A modeling framework for incorporating high-frequency unknown dynamics in the adaptive control framework is suggested. Possible fundamental limitations of existing adaptive control framework is suggested. Possible fundamental limitations of existing adaptive control algorithms are also discussed, with emphasis upon their closed-loop stability properties in the presence of unmodeled high-frequency dynamics.

Athans, M.

Deterministic representation of chaos in classical dynamics

Chaos in an Anosov-type mechanical system is eliminated by referring the governing equations to a specially selected rapidly oscillating (non-inertial) frame of reference in which the stabilization effect is caused by inertia forces. The result is generalized to any orbitally unstable mechanical system.

Zak, M.

Effects of deterministic surface distortions on reflector antenna performance

Systematic distortions of reflector antenna surfaces can cause antenna radiation patterns to be undesirably different from those of perfectly smooth reflector surfaces. In this paper, a simulation model for systematic distortions is described which permits an efficient computation of the effects of distortions in the reflector pattern. The model uses a vector diffraction physical optics analysis for the determination of both the co-polar and cross-polar fields. An interpolation scheme is also presented for the description of reflector surfaces which are prescribed by discrete points. Representative numerical results are presented for reflectors with sinusoidally and thermally distorted surfaces. Finally, comparisons are made between the measured and calculated patterns of a slowly-varying distorted offset parabolic reflector.

Rahmat-Samii, Y.