The book delves into "grey-box" identification in process modeling, emphasizing how it utilizes both invariant prior knowledge and experimental response data to address the challenges posed by partial knowledge and disturbances. This approach aims to enhance model reproducibility, overcoming the limitations of traditional modeling techniques. By integrating these two information sources, the book offers insights into improving the accuracy and reliability of process models.
