Pupillary light reflex system order reduction by Rms Model Order Reduction MATLAB Tool

A new method for the reduction of high-order, linear time invariant systems is proposed. The method is based on the differentiation technique and generates low order stable models retaining both the initial Markov parameters and time-moments, of the original system. Theses biased models give a better approximation for both the steady-state as well as the transient part of the time response. The proposed procedure avoids the necessity of formulating Routh-type arrays, application of reciprocal transformation, finding the time moments of the nth order original system before hand and the use of gain-factor, to generate the denominator and numerator of the models unlike other methods. The new procedure is simple, direct and computationally superior to other methods based on the differentiation technique. The method is well illustrated with pupillary light reflex system. This method is implemented using RMS Model Order Reduction MATLAB Tool and also responses are analysed. In this paper a MATLAB-based tool with a Graphical User Interface (GUI), to compute reduced models of a low damping plants are presented. The model reduction techniques implemented in this tool are based on Different techniques. The method selected in this paper is Hybrid method. Upon execution of the toolbox, a GUI will appear with four frames named "METHODS", "INPUT DATA", "OUTPUTOPTIONS", and "DISPLAYUNIT".