Till now a wide class of aircraft GTE optimization problems has been solved with the help of deterministic approach and it has been quite enough. GTE was considered as ideal system. Strictly speaking, such consideration of any engineering object is incorrect because under the real-life conditions an object is a stochastic system, which has certain indefinites. Therefore the probabilistic estimation of optimization problem results is required.

Let us consider from this point of view the GTE control laws optimization problem. As a control law we consider the dependence of position of a certain GTE controllable element upon a certain GTE mode operation parameter. As an example, for the case of GTE throttle performance optimization one can consider the position dependence upon an engine rotor rotation speed or upon an engine thrust. The optimum laws of control and therefore the optimization criterion extremum value obtained with...

1.
Egorov, I. N., 1992, “Optimization of a Multistage Axial Compressor, Stochastic Approach,” ASME Paper 92-GT-163.
2.
Egorov, I. N., 1993, “Deterministic and Stochastic Optimization of Variable Axial Compressor,” ASME Paper 93-GT-397.
3.
Draper, N. R., and Smith, H., 1981, Applied Regression Analysis, John Wiley & Sons, New York.
4.
Egorov, I. N., et al., 1989, “Procedures of Indirect Statistical Optimization on the Basis of Self-Organization and Their Use in Aircraft GTE. Optimization Problems,” VINITI (2622-B89).
5.
Egorov, I. N., and Kretinin, G. V., 1993, “Optimization of Gas Turbine Engine Elements by Probability Criteria,” ASME Paper 93-GT-191.
6.
Egorov, I. N., 1992, “Optimization of a Multistage Axial Compressor in a Gas-Turbine Engine System,” ASME Paper 92-GT-424.
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