Symbolic Regression based Solution for the Optimal Control Problem with Constraints

Askhat I. Diveev, Oubai Hussein, Elizaveta Shmalko


This article presents a numerical solution to the problem of optimal control of objects in an environment with phase constraints. The proposed approach of synthesized optimal control consists of two steps. First, the problem of synthesizing the stabilization system of an object relative to some point in the state space is solved. The resulting feedback control system is added to the mathematical model of the control object and then the problem of the optimal location of stabilization points, which are essentially attractors, is solved. To solve the synthesis problem, methods of symbolic regression are used, which are completely machine treated, universal and independent of the type of control object. An example of solving the optimal control problem for a group of quadrocopters moving a cargo on flexible rods in a space with constraints is given.

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