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Knowledge-based methods for control systems

Abstract

This thesis consists of three projects which combine artificial intelligence and control. The first part describes an expert system interface for system identification, using the interactive identification program Idpac. The interface works as an intelligent help system, using the command spy strategy. It contains a multitude of help system ideas. The concept of scripts is introduced as a data structure used to describe the procedural part of the knowledge in the interface. Production rules are used to represent diagnostic knowledge. A small knowledge database of scripts and rules has been developed and an example run is shown. The second part describes an expert system for frequency response analysis. This is one of the oldest and most widely used methods to determine the dynamics of a stable linear system. Though quite simple, it requires knowledge and experience of the user, in order to produce reliable results. The expert system is designed to help the user in performing the analysis. It checks whether the system is linear, finds the frequency and amplitude ranges, verifies the results, and, if errors should occur, tries to give explanation and remedies for them. The third part describes three diagnostic methods for use with industrial processes. They  More>>
Authors:
Publication Date:
Dec 31, 1992
Product Type:
Thesis/Dissertation
Report Number:
LUTFD2-TFRT-1040
Reference Number:
SCA: 220400; PA: AIX-24:033322; SN: 93000963290
Resource Relation:
Other Information: TH: Doctoral thesis (TeknD).; PBD: 1992
Subject:
22 GENERAL STUDIES OF NUCLEAR REACTORS; COMPUTERIZED CONTROL SYSTEMS; ARTIFICIAL INTELLIGENCE; EXPERT SYSTEMS; FLOW MODELS; FREQUENCY RESPONSE TESTING; KNOWLEDGE BASE; REAL TIME SYSTEMS; 220400; CONTROL SYSTEMS
OSTI ID:
10135514
Research Organizations:
Lund Univ. (Sweden). Dept. of Automatic Control
Country of Origin:
Sweden
Language:
English
Other Identifying Numbers:
Other: ON: DE93621049; TRN: SE9300028033322
Availability:
OSTI; NTIS; INIS
Submitting Site:
SWDN
Size:
[236] p.
Announcement Date:
Jul 05, 2005

Citation Formats

Larsson, J E. Knowledge-based methods for control systems. Sweden: N. p., 1992. Web.
Larsson, J E. Knowledge-based methods for control systems. Sweden.
Larsson, J E. 1992. "Knowledge-based methods for control systems." Sweden.
@misc{etde_10135514,
title = {Knowledge-based methods for control systems}
author = {Larsson, J E}
abstractNote = {This thesis consists of three projects which combine artificial intelligence and control. The first part describes an expert system interface for system identification, using the interactive identification program Idpac. The interface works as an intelligent help system, using the command spy strategy. It contains a multitude of help system ideas. The concept of scripts is introduced as a data structure used to describe the procedural part of the knowledge in the interface. Production rules are used to represent diagnostic knowledge. A small knowledge database of scripts and rules has been developed and an example run is shown. The second part describes an expert system for frequency response analysis. This is one of the oldest and most widely used methods to determine the dynamics of a stable linear system. Though quite simple, it requires knowledge and experience of the user, in order to produce reliable results. The expert system is designed to help the user in performing the analysis. It checks whether the system is linear, finds the frequency and amplitude ranges, verifies the results, and, if errors should occur, tries to give explanation and remedies for them. The third part describes three diagnostic methods for use with industrial processes. They are measurement validation, i.e., consistency checking of sensor and measurement values using any redundancy of instrumentation; alarm analysis, i.e. analysis of multiple alarm situations to find which alarms are directly connected to primary faults and which alarms are consequential effects of the primary ones; and fault diagnosis, i.e., a search for the causes of and remedies for faults. The three methods use multilevel flow models, (MFM), to describe the target process. They have been implemented in the programming tool G2, and successfully tested on two small processes. (164 refs.) (au).}
place = {Sweden}
year = {1992}
month = {Dec}
}