The application of artificial intelligence techniques for intelligent control of dynamical physical systems

Abstract

There is an increasing concern among the scientific community and industrialists over the safe and reliable operation of control systems in industries. Although several adaptive control techniques have been introduced, they are not robust enough for many real-world problem domains where the degree of uncertainty is high and therefore classical methods of mathematical modelling and control fail. Computer technology has reached a point where machine intelligence can be incorporated in many of the systems that we use daily. Changes in environments, unmeasurable disturbances, changing reference models and performance criteria and component failures are some of the characteristics which necessitate intelligent control. The developments in the field of artificial intelligence have reached a stage which will help to reduce these control complexities by incorporating intelligence into the control systems. In this paper we explain various artificial intelligence techniques that can be used to control dynamical physical systems.

Welcome to 2020 and the Future of Control

“…The ideal would of course be to define a “best” design procedure, knowing that there is considerable latitude in the competing needs, and engineering judgement is more important than optimal figures of merit. Artificial Intelligence and a Machine Learning perspective may help in this type of design question. We may also benefit from further developments in data driven optimal and predictive control methods.…”