Abstract
Frequently the information-control issues in manufacturing automation processes become very complex and cannot be separated from the economic and social issues of large complex systems. In many instances well-defined subsystems are a basic part of the overall system and interconnections and controllers for the total system become critically important. This research recognizes that multiple-connected systems play an important part in the theory of automatic control. One can achieve better results when controlling these systems if more exact and definitive mathematical models can be developed for these processes.Formative methods for static multiple-connected systems have already been developed. However, static models are not effective in a dynamic operating mode. Therefore, the development of dynamic models for multiple-connected sub-systems is considered essential to the design of future systems. Mutual influence among parameters and signals is a typical attribute for such systems. If any parameter changes, this change may affect many signals and the total system itself. Only with the availability of an appropriate dynamic model of the system can one take into account how strong is the influence of a parameter variation or a signal perturbation.
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