System Identification Makes Sense of Complex Measurements

The advancement of computer algorithm and speed has brought about a revolution in modelling and simulation of especially complex systems. Various intelligent methods are available in an easy to use manner for examining and analyzing highly nonlinear systems. This paper demonstrates the elegant application of System Identification technique in processing complex sensor signals and turning them into easily understood and useable measurements. As example, System Identification technique was applied solve a unique issue of grading Agarwood oil which has been based on a manual technique for a long time. For this ground breaking research, data from a chemical analysis of the Agarwood oil, acquired via GCMS measurements, is employed for identification. A single sample of the oil can be represented by hundreds of chemical compounds; these were reduced via a data reduction method. After proper processing of the data thru the System Identification procedure, a valid model was obtained and used to produce a highly accurate grading for the Agarwood oil quality.