An R library for nonlinear black-box system identification

A Qualitative-Fuzzy Framework for Nonlinear Black-Box System Identification

This paper presents a novel approach to nonlinear black-box system identification which combines Qualitative Reasoning (QR) methods with fuzzy logic systems. Such a method aims at building a good initialization of a fuzzy identifier, so that it will converge to the inputoutput relation which captures the nonlinear dynamics of the system. Fuzzy inference procedures should be initialized with a r...

Nonlinear black-box modeling in system identification: a unified overview

A nonlinear black-box structure for a dynamical system is a model structure that is prepared to describe virtually any nonlinear dynamics. There has been considerable recent interest in this area, with structures based on neural networks, radial basis networks, waveiet networks and hinging hyperplanes, as well as wavelet-transform-based methods and models based on fuzzy sets and fuzzy rules. Th...

Black-Box Tool for nonlinear System Identification Based upon Fuzzy System

This paper introduces a novel identifier scheme for identification of non-linear systems with disturbances. The identification process is carried out in two steps; an off-line procedure and an online procedure. The method comprises of an automatic structure generating phase using entropy based technique. The accuracy of the model is suitably controlled using the entropy measure. The parameter l...

Nonlinear Black-box Modeling in System Identiication

Recursive Black-box Identification of Nonlinear State-space ODE Models

Nonlinear system identification methods is a topic that has been gaining interest over the last years. One reason is the many application areas in controller design and system development. However, the problem of modeling nonlinear systems is complex and finding a general method that can be used for many different applications is difficult. This thesis treats recursive identification methods fo...