Many real world systems exhibit a quasi linear or weakly nonlinear behavior during normal operation, and a hard saturation effect for high peaks of the input signal. A typical example of such systems is the cascaded water-tanks benchmark. This benchmark combines soft and hard nonlinearities to be identified based on relatively short data records. In this paper, a methodology to identify an unstructured flexible nonlinear state space model (NLSS) for the cascaded water-tanks benchmark is proposed. The flexibility of the NLSS model structure is demonstrated by introducing two different initialisation schemes. Furthermore the strengths and short-comings of the model structure are discussed with respect to the cascaded water-benchmark identification problem.
- Nonlinear system identification
- Frequency domain identification
- Nonparametric methods