IEEE Transactions on Automatic Control, Vol.65, No.4, 1514-1524, 2020
Extending the Best Linear Approximation Framework to the Process Noise Case
The best linear approximation (BLA) framework has already proven to be a valuable tool to analyze nonlinear systems and to start the nonlinear modeling process. The existing BLA framework is limited to systems with additive (colored) noise at the output. Such a noise framework is a simplified representation of reality. Process noise can play an important role in many real-life applications.This paper generalizes the best linear approximation framework to account also for the process noise, both for the open-loop and the closed-loop setting, and shows that the most important properties of the existing BLA framework remain valid. The impact of the process noise contributions on the robust BLA estimation method is also analyzed.
Keywords:Nonlinear systems;Linear approximation;Kernel;Nonlinear distortion;Analytical models;Additives;Additive noise;Best linear approximation (BLA);nonlinear systems;process noise;system identification