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The system identification procedure is a powerful and flexible tool for the modeling of dynamic systems. This paper implements the theory of parametric identification in order to estimate a valid model of a flexible robotic arm. For this purpose experimental data is used for the estimation of ARMAX SISO models. A two-stages identification procedure (non-parametric & parametric) provides an insight about the system under identification. In the first stage, known signal analysis methods are applied (correlation-spectral analysis) for the estimation of frequencies and frequency response, and in the second stage, the estimation of ARMAX models is performed in order to fit a transfer function model to collected input-output data set. For the estimation of model's coefficients, use of Evolutionary Algorithms is implemented.

Contemporary vehicles have to satisfy high ride comfort criteria. In order to determine appropriate human body model in driving condition field and laboratory investigations on passenger cars have been performed. In field research, dominant vibrations loading of passenger was determined by variance analysis of experimental results. The highest loading is in vertical and the lowest is in lateral direction. These results were base for further laboratory investigations. Group of thirty volunteer subjects was tested. We examined the influence of broadband random vibrations on human body behavior by Seat To Head Transmissibility (STHT) function. The influence of vertical and fore and aft vibrations on occupants were examined separately. In addition to, the influence of multi directional vibration was investigated.