An Input-Output Criterion for Linear Model Deduction

Abstract

Model order deduction algorithms have been developed in an effort to automate the production of accurate, minimal complexity models of dynamic systems in order to aid in the design of these systems. Previous algorithms, MODA and Extended MODA, deduce models independent of system inputs and outputs. FD-MODA uses frequency response methods to deduce models of a single input-output pair. In this paper, an input-output criterion based on controllability and observability is combined with the frequency based criterion used by MODA. The new model deduction algorithm, IO-MODA, compares the ratio of the adjacent diagonal values of the system gramian to a user specified threshold. The gramian is computed from a balanced realization of the system. IO-MODA generates an accurate multiple-input multiple-output model of minimum order with physically meaningful states. This model is called a proper MIMO model. An example problem is used to demonstrate this new model deduction algorithm. [S0022-0434(00)02103-1]