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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Robust eigenstructure assignment by a projection method - Applications using multiple optimization criteria

A methodology for robust eigenstructure assignment for multivariable feedback systems is presented. The algorithm is based upon a pole placement technique using projections onto subspaces of admissible eigenvectors. New ideas are introduced to generate target (desired) sets of unitary eigenvectors and determine optimal feasible eigenvectors in a least-square sense. Useful connections are established between the pole-placement by independent modal space control and the method introduced in this paper. A multicriterion optimization algorithm is also presented, which takes efficient advantage of the present eigenstructure assignment method. These developments show significant improvement over an earlier version of this algorithm in both computational cost and accuracy. This optimization process appears to be numerically robust and suitable for high-dimensional multicriterion optimizations; it is especially attractive for computer-aided design of control systems.

Rew, D. W.↗
NASA NTRS1994

Techniques for designing rotorcraft control systems

Over the last two and a half years we have been demonstrating a new methodology for the design of rotorcraft flight control systems (FCS) to meet handling qualities requirements. This method is based on multicriterion optimization as implemented in the optimization package CONSOL-OPTCAD (C-O). This package has been developed at the Institute for Systems Research (ISR) at the University of Maryland at College Park. This design methodology has been applied to the design of a FCS for the UH-60A helicopter in hover having the ADOCS control structure. The controller parameters have been optimized to meet the ADS-33C specifications. Furthermore, using this approach, an optimal (minimum control energy) controller has been obtained and trade-off studies have been performed.

Yudilevitch, Gil↗
NASA NTRS1999

Further Development, Support and Enhancement of CONDUIT

From the first airplanes steered by handles, wheels, and pedals to today's advanced aircraft, there has been a century of revolutionary inventions, all of them contributing to flight quality. The stability and controllability of aircraft as they appear to a pilot are called flying or handling qualities. Many years after the first airplanes flew, flying qualities were identified and ranked from desirable to unsatisfactory. Later on engineers developed design methods to satisfy these practical criteria. CONDUIT, which stands for Control Designer's Unified Interface, is a modern software package that provides a methodology for optimization of flight control systems in order to improve the flying qualities. CONDUIT is dependent on an the optimization engine called CONSOL-OPTCAD (C-O). C-O performs multicriterion parametric optimization. C-O was successfully tested on a variety of control problems. The optimization-based computational system, C-O, requires a particular control system description as a MATLAB file and possesses the ability to modify the vector of design parameters in an attempt to satisfy performance objectives and constraints specified by the designer, in a C-type file. After the first optimization attempts on the UH-60A control system, an early interface system, named GIFCORCODE (Graphical Interface for CONSOL-OPTCAD for Rotorcraft Controller Design) was created.

Veronica, Moldoveanu↗
NASA NTRSDate not supplied

Multicriterion Design Methods for Aerospace Systems

An efficient method is presented for multi-criterion preliminary design and demonstrated for a tetrahedral truss platform. The present method requires minimal analysis effort and permits rapid estimation of optimized truss behavior for preliminary design. A 14-m-diameter, 3-ring truss platform represents a candidate reflector support structure for space-based science spacecraft. The truss members are divided into 9 groups by truss ring and position. Design variables are the cross-sectional area of all members in a group, and are either 1, 3 or 5 times the minimum member area. Non-structural mass represents the node and joint hardware used to assemble the truss structure. Taguchi methods are used to efficiently identify key points in the set of Pareto-optimal truss designs. Key points identified using Taguchi methods are the maximum frequency, minimum mass, and maximum frequency-to-mass ratio truss designs. Low-order polynomial curve fits through these points are used to approximate the behavior of the full set of Pareto-optimal designs. The resulting Pareto-optimal design curve is used to predict frequency and mass for optimized trusses. Performance improvements are plotted in frequency-mass (criterion) space and compared to results for uniform trusses. Application of constraints to frequency and mass and sensitivity to constraint variation are demonstrated.

taguchi methods↗