This is a paper of expository nature reflecting the author's past experiences, his current research efforts, and his aspirations about the future of automatic-control systems. It is not intended to give a quantitative analysis of modern control methodologies, which may be found in the bibliography at the end of the text, but rather emphasize the importance of a growing area in control engineering. Reviewing the classical, optimal, and stochastic control systems, the reader is led into the uncertainties and controversies of adaptive and learning controls. While self-organizing control was proposed for a systematic unification of these most advanced control methodologies, intelligent control--a discipline capable of high-level decision making and task execution--is predicted as the next level of sophistication in the hierarchy of control systems. A case study on a hierarchically intelligent controlled prosthesis, summarized herein, establishes the feasibility of the suggested methodologies. Future applications to other larse scale systems of general or specific scientific interest may prove the importance of such a discipline.