  Control Systems, particularly closed-loop control systems (CLCS), are
frequently used in production machines, vehicles, and robots nowadays. CLCS are
needed to actively align actual values of a process to a given reference or set
values in real-time with a very high precession. Yet, artificial intelligence
(AI) is not used to model, design, optimize, and tune CLCS. This paper will
highlight potential AI-empowered and -based control system designs and
designing procedures, gathering new opportunities and research direction in the
field of control system engineering. Therefore, this paper illustrates which
building blocks within the standard block diagram of CLCS can be replaced by
AI, i.e., artificial neuronal networks (ANN). Having processes with real-time
contains and functional safety in mind, it is discussed if AI-based controller
blocks can cope with these demands. By concluding the paper, the pros and cons
of AI-empowered as well as -based CLCS designs are discussed, and possible
research directions for introducing AI in the domain of control system
engineering are given.
