This book is an introduction to machine learning control (MLC), a surprisingly simple model-
free methodology to tame complex nonlinear systems. These systems are assumed to be …

We investigate open-and closed-loop active control for aerodynamic drag reduction of a car
model. Turbulent flow around a blunt-edged Ahmed body is examined at Re_ H ≈ 3 * 10^ 5 …

We experimentally optimize mixing of a turbulent round jet using machine learning control
(MLC) following Li et al.(Exp Fluids 58 (article 103): 1–20, 2017). The jet is manipulated with …

The paper is devoted to an emerging trend in control—a machine learning control. Despite
the popularity of the idea of machine learning, there are various interpretations of this …

The problem of control synthesis is considered as machine learning control. The paper
proposes a mathematical formulation of machine learning control, discusses approaches of …

We advance Machine Learning Control (MLC), a recently proposed model-free control
framework which explores and exploits strongly nonlinear dynamics in an unsupervised …

Active drag reduction (DR) of a square-back Ahmed body is experimentally studied based
on machine learning or artificial intelligence (AI) control. The control system consists of four …

Most processes in industry are characterized by nonlinear and time-varying behavior. The
identification of mathematical models typically nonlinear systems is vital in many fields of …

In this paper, the implementation of genetic programming (GP) to design a controller
structure is assessed. GP is used to evolve control strategies that, given the current and …

This paper introduces the application of a genetic programming (GP)-based method for the
automated design and tuning of process controllers, representing a noteworthy …