Robust state estimator design for systems with input-induced nonlinearities: An industrial printer case study

Abstract

The research focuses on a state estimation problem for the paper path and heat flow control of industrial printers. The dynamics of industrial printers can be modeled with a system with input-induced nonlinearities. This model of the system switches in time with a parameter vector which is externally triggered. An important issue in the design of the state estimator involves the question as to what extend the stability and the performance of the estimated dynamics are robust against perturbations and uncertainties in the parameters of the system. For this class of systems we propose the design of an estimator based on an affine parameter dependent representation of the system with parametric uncertainties. The performance of the estimator is analyzed and the stability proven based on Lyapunov theory. Simulation examples show the effectiveness of the proposed approach in the presence of several arbitrary switches between modes.