USE OF REDUCED ORDER MODELS FOR SENSITIVITY PREDICTION OF HIGHER ORDER SYSTEMS

Abstract

The work included in this dissertation deals\ with the sensitivity prediction of higher order systems using reduced order models. The first chapter introduces sensitivity prediction problem and its importance. In this chapter model reduction problem, its necessity and application are also discussed. Role of sensitivity prediction in solving engineering problems is given in chapter-2. In this chapter the general applications of sensitivity prediction are also discussed. Classification and critical review of model reduction techniques in time domain and frequency domain are given in Chapter-3. In Chapter-4, the use of reduced order models for sinsitivity prediction is discussed in detail. Applications of this sensitivity prediction technique are described in Chapter-5. The respective step response of the illustrative examples, taken from Aircraft instrumentation area, are also shown for comparison purpose. The computer programe, in FORTRAN, for sensitivity prediction of higher order systems using reduced order models, has also developed and implemented successfully on a NEXUS-3000 computer system.