Anaerobic digestion process control using a knowledge-based system
| dc.contributor.advisor | Andrews, John F. | |
| dc.creator | Barnett, Michael William | |
| dc.date.accessioned | 2009-06-04T00:27:30Z | |
| dc.date.available | 2009-06-04T00:27:30Z | |
| dc.date.issued | 1989 | |
| dc.description.abstract | Much attention has been devoted to the design and construction of wastewater treatment plants. However, relatively little attention has been devoted to plant operations. Knowledge based or expert systems are oriented toward improving operational procedures and thus have significant potential for solving control problems. This paper presents the results of a study conducted to examine the use of expert systems technology for computer assisted operation of the anaerobic digestion process. Knowledge was divided into mechanistic understanding of the process and that which comes from experience (heuristic). Effective operation requires both types of knowledge. A process task analysis identified four major tasks. These are monitoring, state assessment, control decision and execution tasks. The analysis suggested an expert system configuration consisting of software modules corresponding to these tasks. Development of the state assessment and control action modules was stressed. The capture of mechanistic knowledge was emphasized. Knowledge was represented using if-then rules. Diagnostic rule development was accomplished using computer simulations of hydraulic, organic, toxic and ammonia upsets which could cause process failure. Rules relating to control included decision rules which specified appropriate control actions and fuzzy rules which specified the amount of control. Additional simulations of process upsets were used to examine the behavior of the system. Several different upset states were properly identified and corrected by the system. The control actions used were influent flow control, dilution, organism recycle and acid or base addition. The rule-based approach was found to be flexible and transparent. Theoretical knowledge from the mechanistic model could be converted into a language understood by operations personnel. However, the expressive capabilities of the rule language and the inability to ensure consistency and completeness in the rule base limited the system. An expert system is knowledge intensive and knowledge transfer from the expert to the computer and from the computer to the operator are important factors. Field testing will be needed to validate the rules developed for the expert system. Future research should emphasize the development of a body of knowledge about process operation. Alternative knowledge representations and hybrid systems integrating expert, fuzzy and stochastic control techniques should be studied. In combination these provide powerful tools for solving the problems of control in wastewater treatment. | |
| dc.format.extent | 327 p. | en_US |
| dc.format.mimetype | application/pdf | |
| dc.identifier.callno | Thesis Env. Sci. 1989 Barnett | |
| dc.identifier.citation | Barnett, Michael William. "Anaerobic digestion process control using a knowledge-based system." (1989) Diss., Rice University. <a href="https://hdl.handle.net/1911/16209">https://hdl.handle.net/1911/16209</a>. | |
| dc.identifier.uri | https://hdl.handle.net/1911/16209 | |
| dc.language.iso | eng | |
| dc.rights | Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder. | |
| dc.subject | Sanitary and municipal engineering | |
| dc.subject | Chemical engineering | |
| dc.subject | Civil engineering | |
| dc.title | Anaerobic digestion process control using a knowledge-based system | |
| dc.type | Thesis | |
| dc.type.material | Text | |
| thesis.degree.department | Environmental Science | |
| thesis.degree.discipline | Engineering | |
| thesis.degree.grantor | Rice University | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy |
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