Semi-Invariant Form of Equilibrium Stability Criteria for Systems with One Cosymmetry
2019, Vol. 15, no. 4, pp. 525-531
Author(s): Kurakin L. G., Kurdoglyan A. V.
This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License
Author(s): Kurakin L. G., Kurdoglyan A. V.
The systems of differential equations with one cosymmetry are considered [1]. The ordinary
object for such systems is a one-dimensional continuous family of equilibria. The stability spectrum
changes along this family, but it necessarily contains zero. We consider the nondegeneracy
condition, thus the boundary equilibria separate the family on linearly stable and instable areas.
The stability of the boundary equilibria depends on nonlinear terms of the system.
The stability problem for the systems with one cosymmetry is studied in [2]. The general problem is to apply the stability criteria one needs to compute coefficients of the model system. It is especially difficult if the system has a large dimension, while a number of critical variables may be small. A method for calculating coefficients is proposed in [3].
In this work the expressions for the known stability criteria are proposed in a form convenient for calculation. The explicit formulas of the coefficients of the model system are given in semi-invariant form. They are expressed using the generalized eigenvectors of the linear matrix and its conjugate matrix.
The stability problem for the systems with one cosymmetry is studied in [2]. The general problem is to apply the stability criteria one needs to compute coefficients of the model system. It is especially difficult if the system has a large dimension, while a number of critical variables may be small. A method for calculating coefficients is proposed in [3].
In this work the expressions for the known stability criteria are proposed in a form convenient for calculation. The explicit formulas of the coefficients of the model system are given in semi-invariant form. They are expressed using the generalized eigenvectors of the linear matrix and its conjugate matrix.
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This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License