Multicriteria Optimization of Time Control Laws of Short Take-Off and Vertical Landing Aircraft Power Plant

Abstract

A multicriteria optimization methodology has been discussed to determine time control laws of advanced aircraft gas turbine engines of complex structure. The resulting optimum control laws ensure top improvement of several defined power plant effectiveness criteria in the system of aircraft at transient work modes. The power plant work quality increase effect is attained due to its work process adaptation for numerous requirements from the side of the aircraft. The proposed methodology effectiveness has been shown by the example of optimizing problem solving to determine time control laws of variable elements of short take-off and vertical landing aircraft power plant.

Minimum cost design of a cellular plate loaded by uniaxial compression

“…Hence, to ensure a satisfactory design some trade-off between the objectives is necessary. For this purpose we use the multiobjective approach to optimize the overall efficiency (Egorov 1998;Egorov et al 1997;Egorov and Kretinin 1992;Dulikravich et al 1999).…”

The Technology of Multipurpose Optimization of Gas-Turbine Engines and Their Components

“…In this example the initial compressor's project had been obtained 'by hand' (without use of optimization methods); the optimal designing of uncontrollable compressor had been carried out by criterion of efficiency maximum at designpoint operating mode (nre =1.0); then for this project the optimal control problem had been solved (the criterion was compressors efficiency at n, =0.8); the simultaneous optimization of both design parameters and control laws had been carried out for two operating modes. Our examples of improving engine performance can be found in [Beknev et.al ., 1991;Egorov,1992a;Egorov,1993;Egorov and Kretinin, 1996].…”

Design of Alloy's Concentrations for Optimized Strength, Temperature, Time-to-Rupture, Cost and Weight

“…IOSO uses a multidimensional response surface technique with adaptive global and middle-range multi-point approximation. The self-adapting response surface formulation [6] used by IOSO allows for incorporation of realistic non-smooth variations of experimentally obtained data and allows for accurate interpolation of such data [5,6]. The first stage of IOSO is the creation of approximations of the objective functions.…”

“…Our approach is based on the use and a special adaptation of a stochastic, multi-objective constrained Indirect Optimization based upon Self-Organization (IOSO) algorithm [5,6] . IOSO stochastic multi-objective optimization algorithm allows for concentrations of a number of alloying elements to be optimized so that a finite number of properties (maximum tensile strength, maximum operating temperature, maximum time-until-rupture, minimum weight, minimum cost, etc.)…”