Sanjay Garg

TL;DR: The existing state of engine control and on-board health management is described, and some specific technologies under development that will enable an aircraft propulsion system to operate in an intelligent way-defined as self-diagnostic, self-prognostic,self-optimizing, and mission adaptable are surveyed.

TL;DR: A unified robust multivariable approach to propulsion control design has been developed at NASA Glenn Research Center and an application of these technologies to control design for linear models of an advanced turbofan engine is presented.

TL;DR: In this article, a linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented, specifically addressing the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements.

TL;DR: In this article, the authors investigated the feasibility of using artificial neural networks as control systems for modern, complex aerospace vehicles via an example aircraft control design study, where a controller for an integrated airframe/propulsion longitudinal dynamics model of a modern fighter aircraft was designed to provide independent control of pitch rate and airspeed responses to pilot command inputs.

TL;DR: Evaluation results are presented for a reduced order controller obtained from the improved H¿ control design showing that the control design meets the specified nominal performance objectives as well as provides stability robustness for variations in plant system dynamics with changes in aircraft trim speed within the transition flight envelope.