Model Predictive Control With Single Degree Of Freedom For Low-Level Control

This contribution presents a suboptimal model predictive control with stabilizing terminal conditions and a derivative-free optimization algorithm for a dedicated class of nonlinear systems. Especially electromagnetic actuators represent this class of nonlinear systems. By combining a single degree of freedom in control on the first variable part of the horizon with finite control input sets, recursive feasibility and asymptotic stability rest upon the findings of classical suboptimal model predictive control. The presented optimization strategy is straightforward to implement, does not require external program libraries, and thus addresses industrial applications in particular. Theoretical derivations are supported by numerical evaluations and comparisons to classical model predictive control.