Control Synthesis as Machine Learning Control by Symbolic Regression Methods

The problem of control synthesis is considered as machine learning control. paper proposes a mathematical formulation control, discusses approaches supervised and unsupervised by symbolic regression methods. principle small variation the basic solution presented to set up neighbourhood search increase efficiency Different methods such genetic programming, network operator, Cartesian binary programming are in details. It shown on computational example possibilities technique MLC for obtaining stabilization system mobile robot.