Stefan F. Graebe

TL;DR: A key aspect of the book is the frequent use of real world design examples drawn directly from the authors' industrial experience, represented by over 15 substantial case studies ranging from distillation columns to satellite tracking.

TL;DR: In this paper, the authors present a method for stochastic grey box identification and surveys experiences and lessons of applying it to a number of industrial processes, including the question of what contribution must be expected from the model designer as opposed to what can be formalized in computer algorithms, and an outlook on future plans to resolve present shortcomings.

TL;DR: In this paper, a strategy for stochastic Grey-box identification is presented and a discussion of the advantages and costs of introducing stochastics into the model is discussed. But the authors focus on the contribution of the model designer as opposed to what can be formalized in computer algorithms, and present plans to resolve present shortcomings.

TL;DR: An alternative benchmark, in which participants did not know the true system, which was supplied in the form of scrambled simulation code is reported, which displays the trade-offs inherent in the different approaches and highlights the interplay between robust and adaptive control.

TL;DR: In this article, a nonlinear observer-based controller configuration for a class of nonlinear single-input single-output systems with certain observability and stability properties is presented, where the effect of input disturbances typically present in chemical processes is investigated.