Knowledge-based methods for control systems.

摘要

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). (Atomindex citation 24:033322)