A New Generalized Pole Clustering-Based Model Reduction Technique and Its Application for Design of Controllers

A new model diminution technique is proposed for the reduction of complexity of higher order linear dynamical systems. In this proposed method, a generalized pole clustering technique is used for obtaining the denominator polynomial of the lower order plant and the numerator polynomial is evaluated by applying the Pade approximation technique. The generalized pole clustering algorithm promises the preservation of stability and dominant poles of the actual system in the reduced order plant. The performance error indices such as integral square error (ISE), integral absolute error (IAE), integral time weighted absolute error (ITAE) and relative integral square error (RISE) are used to validate the proposed technique. By using the transfer function of the simplified order plant, the PID and lead/lag compensators are designed by using a moment matching algorithm. This controller is applied to the original large scale system and the response of the closed loop system is matching with the response of the desired reference model.