This report presents two sets of data, suitable for development, testing and benchmarking of system identification algorithms for nonlinear processes. The first data set is recorded from a laboratory process that can be well described by a block oriented nonlinear model. The data set is challenging; it consists of only 500 samples, the nonlinear effect is large and the damping is not too good. The second data set is recorded from a laboratory process known to be governed by nonlinear differential equations.
Note: The software package can be downloaded from http://www.it.uu.se/research/publications/reports/2010-020/NonlinearData.zip
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