Model Predictive Control (MPC) can be dated back to the 1960s, and can now be regarded as a mature control method, which has had significant impact on industrial process control. It is applied in many control systems and has been extended to include non-linear dynamics and non-convex constraints. Of increasing importance in all such control systems in the economic benefits within the design of the system. Traditionally, the so-called control pyramid has been the main technique to do this, whereby economic targets are translated into setpoints and reference trajectories, which are in turn stabilized by control techniques such as MPC. At the same time, in process systems engineering and other fields of application, one aims at economic process operation and much attention has been given to this and the term Economic Model Predictive Control (EMPC) has been coined. Economic Nonlinear Model Predictive Control provides a concise overview of different approaches on the question of stability and optimality in different formulations of EMPC. It is the first monograph to cover approaches both with and without terminal constraints and end penalties, and turnpike/dissipativity-based settings as well as Lyapunov-based approaches. This monograph is an accessible tutorial on the state-of-the-art in model predictive control. Students and researchers will find a clear exposition of current knowledge upon which they can build their own research.

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