Many authors have noted the difficulty of developing the models required for nonlinear
model predictive control (NMPC) and other nonlinear, model-based control strategies. One …

Identification algorithms based on the well-known linear least squares methods of gaussian
elimination, Cholesky decomposition, classical Gram-Schmidt, modified Gram-Schmidt …

Input-output representations of non-linear discrete-time systems are discussed. It is shown
that the NARMAX (Non-linear AutoRegressive Moving Average with eXogenous inputs) …

Hydraulic Servo-systems details the basic concepts of many recent developments of
nonlinear identification and nonlinear control and their application to hydraulic servo …

An orthogonal least squares estimator, which was originally derived for single-input single-
output systems, is extended to multi-input multi-output non-linear systems. The estimator can …

An orthogonal parameter estimation algorithm is derived which allows each parameter in a
linear–in–the–parameters non–linear difference equation model to be estimated …

The present bibliography represents a comprehensive list of references on nonlinear system
identification and its applications in signal processing, communications, and biomedical …

The series Advances in Industrial Control aims to report and encourage technology transfer
in control engineering. The rapid development of control technology has an impact on all …

Conventional methods for the structural nondestructive testing (NDT) such as pulsed eddy
current (PEC), ultrasonic detection (UT), and so on are based on the output signal …

Takens Embedding Theorem forms the basis of virtually all approaches to the analysis of
time series generated by nonlinear deterministic dynamical systems. It typically allows us to …