In this article we review the growth and development of control engineering, leading to modern adaptive methods and finally to autonomous intelligent control. Although the use of feedback control can be traced back to ancient and medieval times, it is really during the 20th century, with the evolution of the electronics age, that control engineering has become a recognized discipline. Well-established methods to model and control plants with linear characteristics and unchanging parameters are already in existence. Nonlinear plants with time-varying internal parameters are more challenging and the so-called ''adaptive'' methods have been developed to address this issue. The abundance of powerful computers has led us to think, in terms of controllers that can ''learn'' using AI techniques such as expert systems, genetic algorithms, neural networks, etc. These paradigms have evolved mostly from studying biological learning processes. ''Intelligent control'' and ''neurocontrol'' are terms that are recognized in the literature today as methods distinct from the more ''conventional'' control methods of the past few decades. Future advances in this science will be in the direction of: the development of controllers that can learn to improve their performance and to plan while they learn a particular task.
|Number of pages||7|
|Journal||IEEE Control Systems|
|Publication status||Published - Oct 1996|