Identification of continuous systems

TLDR: This book discusses the role of Nonparametric Models in Continuous System Identification, and methods for Obtaining Transfer Functions from nonparametric models using the Frequency-Domain approach.

Abstract: Introduction. Continuous-Time Models of Dynamical Systems. Nonparametric Models. Parametric Models. Stochastic Models of Linear Time-Invariant Systems. Models of Distributed Parameter Systems (DPS). Signals and their Representations. Functions in the Ordinary Sense. Distribution or Generalized Functions. Identification of Linear Time-Invariant (LTIV) Systems via Nonparametric Models. The Role of Nonparametric Models in Continuous System Identification. Test Signals for System Identification. Identification of Linear Time-Invariant Systems - Time-Domain Approach. Frequency-Domain Approach. Methods for Obtaining Transfer Functions from Nonparametric Models. Numerical Transformations between Time- and Frequency-Domains. Parameter Estimation for Continuous-Time Models. The Primary Stage. The Secondary Stage: Parameter Estimation. Identification of Linear Systems Using Adaptive Models. Gradient Methods. Frequency-Domain. Stability Theory. Linear Filters. Identification of Multi-Input Multi-Output (MIMO) Systems, Distributed Parameter Systems (DPS) and Systems with Unknown Delays and Nonlinear Elements. MIMO Systems. Time-Varying Parameter Systems (TVPS). Lumped Systems with Unknown Time-Delays. Identification of Systems with Unknown Nonlinear Elements. Identification of Distributed Parameter Systems. Determination of System Structure. Index.