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Results for “parameter optimization”
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Optimized Parameters for McClain Correlation in GlennICE
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Necessary conditions for discrete parameter stochastic optimization problems
Discrete parameter stochastic optimization problems necessary conditions, deriving maximum principle
Necessary conditions for continuous parameter stochastic optimization problems
Continuous parameter stochastic optimization principle using abstract variational theory
Optimization of ''ephemeridal'' parameters for minimum propellant requirements on multiplanet roundtrip swingby-stopover missions.
Ephemeridal parameter optimization for minimum propellant requirements for round trip swingby- stopover multiplanet mission
Optimal estimation in the presence of unknown parameters.
Optimal estimation of sampled stochastic process with finite state unknown parameters
Optimal control of plants with random slowly- varying parameters.
Optimal control of plants with random slowly varying parameters having known probability density function
Optimal control of plants with random slowly-varying parameters
Optimal control of plants with random slowly varying parameters
Parametric study of critical constraints for a canard configured medium range transport using conceptual design optimization
Constrained parameter optimization was used to perform optimal conceptual design of both canard and conventional configurations of a medium range transport. A number of design constants and design constraints were systematically varied to compare the sensitivities of canard and conventional configurations to a variety of technology assumptions. Main landing gear location and horizontal stabilizer high-lift performance were identified as critical design parameters for a statically stable, subsonic canard transport.
Optimal adaptive filter realizations for sampled stochastic processes with an unknown parameter
Optimal adaptive filter for sampled stochastic processes with unknown parameter
Necessary conditions for discrete parameter stochastic optimization problems
Necessary conditions for discrete parameter stochastic optimization problems
Optimal design procedures for two-level fractional factorial experiments given partial prior information about parameters
Optimal design procedure as experimental design finite decision problem, using Bayes and minimax techniques
Necessary conditions for continuous parameter stochastic optimization problems
Abstract variational theory application to continuous parameter stochastic optimization problems to derive maximum principles in linear programming
Bayes and minimax controllers for a linear system with stochastic jump parameters
Optimal zero-memory regulator for linear system with stochastic jump parameters, considering Bayes and minimax controllers
Inverse problems in the design, modeling and testing of engineering systems
Formulations, classification, areas of application, and approaches to solving different inverse problems are considered for the design of structures, modeling, and experimental data processing. Problems in the practical implementation of theoretical-experimental methods based on solving inverse problems are analyzed in order to identify mathematical models of physical processes, aid in input data preparation for design parameter optimization, help in design parameter optimization itself, and to model experiments, large-scale tests, and real tests of engineering systems.
Preparation and Analysis of Platinum Thin Films for High Temperature Sensor Applications
A study has been made of platinum thin films for application as high temperature resistive sensors. To support NASA Glenn Research Center s high temperature thin film sensor effort, a magnetron sputtering system was installed recently in the GRC Microsystems Fabrication Clean Room Facility. Several samples of platinum films were prepared using various system parameters to establish run conditions. These films were characterized with the intended application of being used as resistive sensing elements, either for temperature or strain measurement. The resistances of several patterned sensors were monitored to document the effect of changes in parameters of deposition and annealing. The parameters were optimized for uniformity and intrinsic strain. The evaporation of platinum via oxidation during annealing over 900 C was documented, and a model for the process developed. The film adhesion was explored on films annealed to 1000 C with various bondcoats on fused quartz and alumina. From this compiled data, a list of optimal parameters and characteristics determined for patterned platinum thin films is given.
A reliable algorithm for optimal control synthesis
In recent years, powerful design tools for linear time-invariant multivariable control systems have been developed based on direct parameter optimization. In this report, an algorithm for reliable optimal control synthesis using parameter optimization is presented. Specifically, a robust numerical algorithm is developed for the evaluation of the H(sup 2)-like cost functional and its gradients with respect to the controller design parameters. The method is specifically designed to handle defective degenerate systems and is based on the well-known Pade series approximation of the matrix exponential. Numerical test problems in control synthesis for simple mechanical systems and for a flexible structure with densely packed modes illustrate positively the reliability of this method when compared to a method based on diagonalization. Several types of cost functions have been considered: a cost function for robust control consisting of a linear combination of quadratic objectives for deterministic and random disturbances, and one representing an upper bound on the quadratic objective for worst case initial conditions. Finally, a framework for multivariable control synthesis has been developed combining the concept of closed-loop transfer recovery with numerical parameter optimization. The procedure enables designers to synthesize not only observer-based controllers but also controllers of arbitrary order and structure. Numerical design solutions rely heavily on the robust algorithm due to the high order of the synthesis model and the presence of near-overlapping modes. The design approach is successfully applied to the design of a high-bandwidth control system for a rotorcraft.