**9. Conclusions**

This work presents the statement of the new optimal control problem with uncertainty. In this problem, the mathematical model of the control object includes an additive limited perturbing function simulating possible model inaccuracies. It is necessary to find an optimal control function that provides for limited perturbations bounded variation of functional value. For this purpose, it is proposed to use the synthesized optimal control method. According to this method initially, the control synthesis problem is solved. After that, in the state space a stable equilibrium point appears. In the second stage, the original optimal control problem is solved by searching positions of some stable equilibrium points, which are a control for stabilization system, obtained in the first stage. It is shown that such an approach supplies the property of a contraction mapping for differential equations of the mathematical model of the plant. Such differential equations are quite feasible, and their solutions reduce the errors of determining the state vector. For the solution of the control synthesis problem it is proposed to apply symbolic regression methods. A comparative example is presented. Computational experiments showed that the obtained solution is very less sensitive to perturbations in the mathematical model of the control object than the direct solution of the optimal control problem.
