Control strategy for systems with input-induced nonlinearities: A printing system case study

The paper discusses economic performance design under nonlinear dynamic behavior and changing operating conditions. Two methods to control plants with input-induced nonlinearities in the presence of hard constraints are presented. A nonlinear predictive controller is designed based on a nonlinear dynamic parameter-dependent model of the system for tracking control. Next a decomposition of the model of the plant is made which allows nonlinear optimal static feedforward and linear dynamic feedback. Model predictive control (MPC) was selected to control the transients while satisfying all constraints without loss of performance. The control scheme has been applied on an industrial printing system. Simulation examples show the effectiveness of the proposed approaches in the presence of variation in the input print queue and constraints.