Abstract

The paper considers methods for estimating stability using Lyapunov functions, which are used for nonlinear polynomial control systems. The apparatus of the Gro¨bner basis method is used to assess the stability of a dynamical system. A description of the Gro¨bner basis method is given. To apply the method, the canonical relations of the nonlinear system are approximated by polynomials of the components of the state and control vectors. To calculate the Gro¨bner basis, the Buchberger algorithm is used, which is implemented in symbolic computation programs for solving systems of nonlinear polynomial equations. The use of the Gro¨bner basis for finding solutions of a nonlinear system of polynomial equations is considered, similar to the application of the Gauss method for solving a system of linear equations. The equilibrium states of a nonlinear polynomial system are determined as solutions of a nonlinear system of polynomial equations. An example of determining the equilibrium states of a nonlinear polynomial system using the Gro¨bner basis method is given. An example of finding the critical points of a nonlinear polynomial system using the Gro¨bner basis method and the Wolfram Mathematica application software is given. The Wolfram Mathematica program uses the function of determining the reduced Gro¨bner basis. The application of the Gro¨bner basis method for estimating the attraction domain of a nonlinear dynamic system with respect to the equilibrium point is considered. To determine the scalar potential, the vector field of the dynamic system is decomposed into gradient and vortex components. For the gradient component, the scalar potential and the Lyapunov function in polynomial form are determined by applying the homotopy operator. The use of Gro¨bner bases in the gradient method for finding the Lyapunov function of a nonlinear dynamical system is considered. The coordination of input-output signals of the system based on the construction of Gro¨bner bases is considered.

Highlights

  • Accepted September 1, 2021 e paper considers methods for estimating stability using Lyapunov functions, which are used for nonlinear polynomial control systems. e apparatus of the Grobner basis method is used to assess the stability of a dynamical system

  • The scalar potential and the Lyapunov function in polynomial form are determined by applying the homotopy operator. e use of Grobner bases in the gradient method for nding the Lyapunov function of a nonlinear dynamical system is considered. e coordination of input-output signals of the system based on the construction of Grobner bases is considered

  • Introduction e most of the dynamical systems in technology and nature are nonlinear dynamical systems. e canonical relations of a nonlinear system can be approximated by polynomials of the components of the state and control vectors

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Summary

THEORY OF COMPUTING e Investigation of Nonlinear Polynomial Control Systems

Accepted September 1, 2021 e paper considers methods for estimating stability using Lyapunov functions, which are used for nonlinear polynomial control systems. e apparatus of the Grobner basis method is used to assess the stability of a dynamical system. Accepted September 1, 2021 e paper considers methods for estimating stability using Lyapunov functions, which are used for nonlinear polynomial control systems. An example of determining the equilibrium states of a nonlinear polynomial system using the Grobner basis method is given. An example of nding the critical points of a nonlinear polynomial system using the Grobner basis method and the Wolfram Mathematica application so ware is given. E application of the Grobner basis method for estimating the a raction domain of a nonlinear dynamic system with respect to the equilibrium point is considered. The scalar potential and the Lyapunov function in polynomial form are determined by applying the homotopy operator. E use of Grobner bases in the gradient method for nding the Lyapunov function of a nonlinear dynamical system is considered. МОДЕЛИРОВАНИЕ И АНАЛИЗ ИНФОРМАЦИОННЫХ СИСТЕМ, ТОМ 28, No 3, 2021 сайт журнала: www.mais-journal.ru

Исследование нелинейных полиномиальных систем управления
ИНФОРМАЦИЯ ОБ АВТОРАХ
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