Non-linear system identification using Hammerstein and non-linear feedback models with piecewise linear static maps
From MaRDI portal
Publication:3151512
DOI10.1080/00207170110089798zbMath1039.93015OpenAlexW2114736631MaRDI QIDQ3151512
Dennis S. Bernstein, Tobin H. Van Pelt
Publication date: 16 October 2002
Published in: International Journal of Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207170110089798
Related Items (8)
Identification of block-oriented nonlinear systems starting from linear approximations: a survey ⋮ Output-only identification of self-excited systems using discrete-time Lur'e models with application to a gas-turbine combustor ⋮ Identification of a class of precision motion systems with uncertain hysteretic nonlinearities ⋮ Quasiconvexity analysis of the Hammerstein model ⋮ A subspace algorithm for simultaneous identification and input reconstruction ⋮ Identification of neuro-fractional Hammerstein systems: a hybrid frequency-/time-domain approach ⋮ Bounding the parameters of block‐structured nonlinear feedback systems ⋮ Computationally efficient identification of continuous-time Lur'e-type systems with stability guarantees
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems
- Identification of systems containing linear dynamic and static nonlinear elements
- Nonlinear black-box modeling in system identification: A unified overview
- Nonlinear black-box models in system identification: Mathematical foundations
- Uniqueness of a basic nonlinear structure
- A generalized canonical piecewise-linear representation
- Non-linear systems identification using radial basis functions
- Fading memory and the problem of approximating nonlinear operators with Volterra series
- Nonlinear regulation: The piecewise linear approach
- The complete canonical piecewise-linear representation. I. The geometry of the domain space
- Identification and analysis of non-linear systems by tensor techniques
- Identification of discrete Hammerstein systems by the Fourier series regression estimate
- Non-parametric orthogonal series identification of Hammerstein systems
- Explicit construction of quadratic Lyapunov functions for the small gain, positivity, circle, and popov theorems and their application to robust stability. Part I: Continuous‐time theory
- Explicit construction of quadratic lyapunov functions for the small gain, positivity, circle, and popov theorems and their application to robust stability. part II: Discrete‐time theory
- Recursive identification of continuous-time Wiener systems
- Measurement and identification of nonlinear systems consisting of linear dynamic blocks and one static nonlinearity
- Piecewise linear identification of non-linear systems
- Nonlinear control design for a Hammerstein model system
- BPD computation and model reference adaptive control (MRAC) of Hammerstein plants
This page was built for publication: Non-linear system identification using Hammerstein and non-linear feedback models with piecewise linear static maps
