MVP-CA Technology for Mission Rule Set Development and Case-Based Retrieval

In spacecraft telemetry, expert systems technology is being used to manage the complexity generated by the greater number of complex measurands. However, an uncontrolled proliferation of rules in an expert system can lead to maintenance, management and retrieval problems of the rulesets. A semi-automated tool, such as Pragati's MVP-CA (Multi-ViewPoint Clustering Analysis) tool, can provide a valuable aid for comprehension, maintenance, integration and evolution of these expert systems by structuring a large knowledge base in various meaningful ways. In this proposal, we seek to determine the feasibility of applying this technology to large, complex spacecraft mission expert systems so as to allow reliable software maintenance and management on them as well as study how these rule sets generated through the MVP-CA tool could be retrieved easily and efficiently through case-based reasoning techniques. Our focus in this project will be to provide relevant information for retrieval maintenance and management of the rule stets through cluster interface definitions which in turn will form the bridge between the MVP-CA tool and case-based reasoning tools. The latter will be used for rule set retrieval for reuse, maintenance and management of the telemetry expert systems.