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The purpose of this paper is to develop a fairly general approach to adaptive control systems which, at the same time, can be mechanized in a reasonable fashion. The development is carried out initially for a simple system with a linear time variant physical process and then extended to the general linear time variant case. Examples are given. A combined learning model and model referenced time variant system is considered next. Finally, the extension of this adaptive concept to control systems which have nonlinear time variant physical processes is presented. Numerous practical implications of the theory are developed in such fields as aerospace vehicle guidance and control, process control, etc. For instance, in re-entry eters of the controlled vehicle vary by two orders of magnitude, while the vehicle dynamic response must remain relatively constant.
Date of Publication: Sept. 1963