D. Zhai, D.K. Rollins, Sr., and N. Bhandari
Nonlinear systems, continuous-time modelling, sinusoidal input se-quence, Hammerstein and Wiener models
Discrete-time modelling (DTM) dominates the systems engineering literature in the applications of block-oriented modelling. The discrete environment of computer-based process control systems and discrete sampling are two major reasons [1]. Also, a DTM is easier to obtain because all input changes are approximated by piecewise step input sequences. Nonetheless, DTM has (potentially) two critical drawbacks relative to continuous-time modelling (CTM). DTM requires constant and frequent sampling and can only predict at those points. DTM is not potentially as accurate as CTM because, at best, it can only approximate continuous-time processes. For Hammerstein and Wiener CTM, this article proposes compact CTM algorithms under sinusoidal input sequences for Hammerstein and Wiener modelling. The proposed method depends only on the most previous input changes and provides exact solutions that are applicable to multiple-input, multiple-output systems as demonstrated.
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