Assessment and Future Directions of Nonlinear Model Predictive Control

The past three decades have seen rapid development in the area of model predic-

tive control with respect to both theoretical and application aspects. Over these

30 years, model predictive control for linear systems has been widely applied,

especially in the area of process control. However, today’s applications often

require driving the process over a wide region and close to the boundaries of op-

erability, while satisfying constraints and achieving near-optimal performance.

Consequently, the application of linear control methods does not always lead to

satisfactory performance, and here nonlinear methods must be employed. This

is one of the reasons why nonlinear model predictive control (NMPC) has en-

joyed significant attention over the past years, with a number of recent advances

on both the theoretical and application frontier. Additionally, the widespread

availability and steadily increasing power of today’s computers, as well as the

development of specially tailored numerical solution methods for NMPC, bring

the practical applicability of NMPC within reach even for very fast systems. This

has led to a series of new, exciting developments, along with new challenges in

the area of NMPC.

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