Aim. Improving of accuracy parameters and reducing of sensitivity to changes of plant parameters for nonlinear robust tank main armament guidance and stabilization electromechanical systems based on synchronous motor with permanent magnets and vector control. Methodology. The method of multiobjective synthesis of nonlinear robust control by nonlinear tank main armament stabilization electromechanical system taking into account the elastic oscillations of the tank gun barrel as a discretecontinuous plant and with parametric uncertainty based on the multiobjective optimization. The target vector of robust control choice by solving the corresponding multicriterion nonlinear programming problem in which the calculation of the vectors of the objective function and constraints is algorithmic and associated with synthesis of nonlinear robust controllers and modeling of the synthesized system for various modes of operation of the system, with different input signals and for various values of the plant parameters. Synthesis of nonlinear robust controllers and non-linear robust observers reduces to solving the system of Hamilton-Jacobi-Isaacs equations. Results. The results of the synthesis of a nonlinear robust tank main armament guidance and stabilization electromechanical systems are presented. Comparison of the dynamic characteristics of the synthesized tank main armament stabilization electromechanical systems showed that the use of synthesized nonlinear robust controllers allowed to improve the accuracy parameters and reduce the sensitivity of the system to changes of plant parameters in comparison with the existing system. Originality. For the first time carried out the multiobjective synthesis of nonlinear robust tank main armament stabilization electromechanical systems. Practical value. Practical recommendations are given on reasonable choice of the gain matrix for the nonlinear feedbacks of the regulator and the nonlinear observer of the tank main armament stabilization electromechanical systems, which allows improving the dynamic characteristics and reducing the sensitivity of the system to plant parameters changing in comparison with the existing system. References 24, figures 1.