Uncertain Systems Order Reduction by Modal Analysis Approach

Objectives: Modeling of physical systems results in complex higher-order representation. It’s somewhat strenuous to process out with these intricate systems, in such conditions these large scale systems are approximated by relegated order model. Methods/Statistical Analysis: A system with bounded parameters but uncertain and having constant coefficients is termed as an interval system. In this jotting Modal analysis approach, order reduction technique has been used to demote the higher order system to its relegated order. Numerical examples are solved to show the supremacy of this advanced technique. Findings: By using the proposed method, the step response of original and reduced order uncertain systems are closer when compared to other methods. The relative integral square error values are also less as compared to other techniques. Application/Improvements: The relegated model acquired by this approach has its behavior homogeneous to the original system. The stability is vowed if the original system is stable. In order to depiction a controller for a higher order system it is quite arduous, so by using the order demotion technique it becomes more facile.