The Space Station Module Power Management and Distribution (SSM/PMAD) testbed system uses cooperating expert systems to autonomously manage the power distribution process. There are several cooperating expert systems continually interacting to provide this management. Whenever other subsystems activities are considered, they also must provide either portions of or complete autonomous management elements which can interact with other subsystems. This poses two problems. First, how do the subsystems agree on an acceptable level of performance; and, second, how do the autonomous management elements determine relative levels of importance amongst each other. Martin Marietta, through its independent research, and under contract to NASA George C. Marshall Space Flight Center since 1985, is continuing the development of these technologies and methodologies for use in the SSM/PMAD and other platforms for automation.Organizing the subsystems and their associated elements into a cohesive and consistent picture requires new approaches. These new approaches include visualizing the ranking of each subsystem's activities and further ranking the complete system level activity and goals. Management of the goals at each subsystem may be done using the priority tensor based approach used in the SSM/PMAD testbed. Ranking the complete system activity requires an integration activity that is capable of dynamically ascertaining and managing a subsystem's relative fundamental relation to the other subsystems; thus, forming a complete rank ordered listing of all the subsystems within the system. How the complete system ranking may be achieved and how an individual subsystem's internal priorities may be managed within the complete system are examined in this paper. Further, how these results may be used in the integration and performance leveling of the autonomously managed system are also presented.