Controller Design for Systems Suffering Nonlinear Distortions

The aim of the study presented in this paper is to provide some initial results over the potential use of best linear approximation models in the design of model-based linear controllers for systems suffering nonlinear distortions. This is illustrated on a nonlinear mechanical resonating system. Parametric best linear approximation models are estimated from frequency response function measurements using random phase multisines. A full nonlinear model for the system is also estimated. This provides the basis for the design of simple optimal linear controllers, and the performance obtained from the controllers based on the nonlinear model is set as the benchmark. Parametric linear models are also estimated from measurements taken using Schroeder phase multisine signals and controllers based on these models are designed. It is shown that in the presence of nonlinear distortions the choice of input excitation in estimating models that describe the best linear approximation to the nonlinear system is crucial. It is also shown that this choice will have an effect on the performance of the model-based controllers. Copyright © 2003 IFAC