Modeling of real time system posses a large number of problems. It is a challenging task to model accurately a large real time system. Modeling of large real time systems results in large number of differential or difference equations that lead to state variable or transfer function models that represents a higher order system. It is very difficult to handle such a higher order system model for the analysis and design purposes. This paper presents an overview of time domain techniques that can be used to reduce the higher order model to a lower order one. The requirement of model order reduction is that the reduced order model so obtained should retain the important and key qualitative and quantitative properties such as stability, transient and steady state response etc. of the original system.

1. R. Prasad, ‘Analysis and design of control system using reduced order models’, PhD. Thesis Department of Electrical Engineering, University of Roorkee, Feb. 1989.
2. A. Gruca and P. Bertrand, ‘Approximation of higher order systems by low order models with delays’, Int. J. Control, No. 6, 1978, pp. 953-965.
3. J. E. Davison, ‘A new method for simplifying large linear dynamic systems’, IEEE Trans., Automat. Control, vol. AC-13, April, 1968, pp. 214-215.
4. M. Avoki, ‘Control of large dynamic system by aggregation’, IEEE Trans., Automat. Control, vol. AC-13, 1968, pp. 246-256.
5. M. Avoki, ‘Control of large scale dynamic systems by aggregation’, IEEE Trans. Automat. Control, vol. AC-13, 1986, pp. 246-253.
6. K. Ogata, ‘Modern Control Engineering’, PHI. Pvt. Ltd., 2nd Edition, 2004.

Model Order Reduction Modal Analysis Approach