Mixed method of model reduction for uncertain systems

A mixed method for reducing a higher order uncertain system to a stable reduced order one is proposed. Interval arithmetic is used to construct a generalized Routh table for determining the denominator polynomial of the reduced system. The reduced numerator polynomial is obtained using factor division method and the steady state error is minimized using gain correction factor. The proposed method is illustrated using a numerical example

Anderson Corollary Based on New Approximation Method for Continuous Interval Systems

In this research, a new technique is developed for reducing the order of high-order continuous interval systems. The model denominator is derived using Anderson corollary and Routh table. Numerator is derived by matching the formulated Markov parameters (MPs) and time moments (TMs). Distinctive features of the proposed approach are: (i) New and simpler expressions for MPs and TMs; (ii) Retaining not only TMs but also MPs while deriving the model; (iii) Minimizing computational complexity while preserving the essential characteristics of system; (iv) Ensuring to produce a stable model for stable system; (v) No need to invert the system transfer function denominator while obtaining the TMs and MPs; and (vi) No need to solve a set of complex interval equations while deriving the model. Two single-input-singleoutput test cases are considered to illustrate the proposed technique. Comparative analysis is also presented based on the results obtained. The simplicity and effectiveness of the proposed technique are established from the simulation outcomes achieved