A quantum optimization approach to Nonlinear Model Predictive Control

We propose a quantum computing approach for the solution of NMPC optimization problems. Assuming the availability of an efficient quantum computer, the approach can considerably decrease the computational time and/or enhance the solution quality compared to classical algorithms. The approach is illustrated by means of a simulation example, concerned with automated driving. The results show that the approach can substantially reduce the computational cost of optimization-based methods.