Nonlinear system identification using heterogeneous multiple models

Nonlinear System Identification Using Heterogeneous Multiple Models

Multiple models are recognised by their abilities to accurately describe nonlinear dynamic behaviours of a wide variety of nonlinear systems with a tractable model in control engineering problems. Multiple models are built by the interpolation of a set of submodels according to a particular aggregation mechanism, with the heterogeneous multiple model being of particular interest. This multiple ...

Adaptive Control of Nonlinear Systems Using Multiple Identification Models

Nonlinear system modeling and identification using Volterra-PARAFAC models

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Robust nonlinear system identification using neural-network models

We study the problem of identification for nonlinear systems in the presence of unknown driving noise, using both feedforward multilayer neural network and radial basis function network models. Our objective is to resolve the difficulty associated with the persistency of excitation condition inherent to the standard schemes in the neural identification literature. This difficulty is circumvente...

Nonlinear System Identification Using Wavelet based SDP Models

System identi…cation has played an increasingly dominant role in a wide range of engineering applications. While linear system’s theory is mature, nonlinear system identi…cation remains an open research area in recent years. This thesis develops a new, e¢ cient and systematic approach to the identi…cation of nonlinear dynamic systems using wavelet based State Dependent Parameter (SDP) models, f...