In this chapter, we introduce the nonlinear model predictive control algorithm in a rigorous
way. We start by defining a basic NMPC algorithm for constant reference and continue by …

We present a technique for computing stability and performance bounds for unconstrained
nonlinear model predictive control (MPC) schemes. The technique relies on controllability …

This paper provides a survey on recent results on NMPC without terminal constraints. We
investigate stability, performance and feasibility issues, both for classical stabilizing NMPC …

For discrete time nonlinear systems satisfying an exponential or finite time controllability
assumption, we present an analytical formula for a suboptimality estimate for model …

This article presents a data-driven control strategy for nonlinear dynamical systems,
enabling the construction of a Koopman-based linear system associated with nonlinear …

Hydrogen produced by microorganisms has been considered as a potential solution for
sustainable hydrogen production for the future. In the current study, an advanced real-time …

With today's worldwide competition, manufacturing companies are faced with challenges to
respond to volatile market demands quickly and flexibly while maintaining a cost-effective …

In this thesis we are concerned with receding horizon control (RHC), also known as model
predictive control. In particular, schemes which neither incorporate terminal constraints nor …

We analyze nominal NMPC schemes without stabilizing terminal constraints in which the
online optimization is terminated prior to convergence to the optimum. We state a new …

Abstract Model Predictive Control (MPC) is a well-established approach to solve infinite
horizon optimal control problems. Since optimization over an infinite time horizon is …