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An expert system approach for the control of a bioprocess. I: Knowledge representation and processing
Author(s) -
Hitzmann Bernd,
Lübbert Andreas,
Schügerl Karl
Publication year - 1992
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.260390107
Subject(s) - bioprocess , knowledge representation and reasoning , computer science , expert system , representation (politics) , automation , a priori and a posteriori , knowledge based systems , process (computing) , operator (biology) , domain knowledge , control (management) , artificial intelligence , machine learning , engineering , programming language , mechanical engineering , philosophy , biochemistry , chemistry , epistemology , repressor , chemical engineering , politics , law , political science , transcription factor , gene
For the control of bioprocesses, a priori knowledge exists which cannot be readily incorporated as a mathematical model but which can be represented by language‐based rules, such as “IF/THEN” conditions. This knowledge is usually implemented via a process operator for the automation of the fermentation. A knowledge‐based system has been developed which can use this kind of knowledge and which is complemented by algorithmic systems, such as statistical analyses and mathematical modeling, for the supervision and control of a bioprocess. In this article, a description of this system is presented. Furthermore, the following features of the system are discussed in detail which are especially important for the development of real‐time, on‐line, knowledge‐based systems: the representation of time‐dependent knowledge; processing of imprecise, uncertain, and incomplete knowledge; the combination of shallow reasoning with model‐based reasoning; informing the bioprocess operator about the inferences and decisions; the demands of the diversity of the knowledge handling; performance; and maintenance and extension of the system.