The subject of the book is to present the modeling, parameter estimation
and other aspects of the identification of nonlinear dynamic systems.
The treatment is restricted to the input-output modeling approach.
Because of the widespread usage of digital computers discrete time
methods are preferred. Time domain parameter estimation methods are
dealt with in detail, frequency domain and power spectrum procedures are
described shortly. The theory is presented from the engineering point of
view, and a large number of examples of case studies on the modeling and
identifications of real processes illustrate the methods. Almost all
processes are nonlinear if they are considered not merely in a small
vicinity of the working point. To exploit industrial equipment as much
as possible, mathematical models are needed which describe the global
nonlinear behavior of the process. If the process is unknown, or if the
describing equations are too complex, the structure and the parameters
can be determined experimentally, which is the task of identification.
The book is divided into seven chapters dealing with the following
topics: 1. Nonlinear dynamic process models 2. Test signals for
identification 3. Parameter estimation methods 4. Nonlinearity test
methods 5. Structure identification 6. Model validity tests 7. Case
studies on identification of real processes Chapter I summarizes the
different model descriptions of nonlinear dynamical systems.