Extending the Best Linear Approximation Framework to the Process Noise Case
This work addresses a limitation of the BLA framework for researchers analyzing nonlinear systems with process noise, but the extension is incremental as it builds directly on existing theory.
The paper extends the Best Linear Approximation (BLA) framework to handle process noise in both open-loop and closed-loop systems, showing that key properties of the original framework remain valid.
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.