Abstract
The paper devotes to a new conception ”Machine learning control”. The mathematical formulation of this term is presented. It is shown, that a numerical method for solution of the control general synthesis problem belongs to the machine learning control. In common case the machine learning control is a search some control function. There are two approaches to this problem. First approach consists of definition of the function with accuracy to some unknown parameters. A search of these parameters is a machine learning. Artificial neural network technology belongs to the first approach. The second approach consists of search mathematical expression of control function by computer. This is a search of function structure and parameters together. Now so far there is only one way to realize this approach. It is symbolic regression. The paper describes symbolic regression technology in common case and some examples of symbolic regression applications for the control synthesis problem are presented.
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