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A method is L-stable if it is A-stable and () as , where is the stability function of the method (the stability function of a Runge–Kutta method is a rational function and thus the limit as + is the same as the limit as ).
The quadratic function () = is a Lyapunov function that can be used to verify stability. Theorem (discrete time version). Given any Q > 0 {\displaystyle Q>0} , there exists a unique P > 0 {\displaystyle P>0} satisfying A T P A − P + Q = 0 {\displaystyle A^{T}PA-P+Q=0} if and only if the linear system x t + 1 = A x t {\displaystyle x_{t+1}=Ax ...
The small-gain theorem gives a sufficient condition for finite-gain stability of the feedback connection. The small gain theorem was proved by George Zames in 1966. It can be seen as a generalization of the Nyquist criterion to non-linear time-varying MIMO systems (systems with multiple inputs and multiple outputs).
For asymptotic stability, the state is also required to converge to =. A control-Lyapunov function is used to test whether a system is asymptotically stabilizable , that is whether for any state x there exists a control u ( x , t ) {\displaystyle u(x,t)} such that the system can be brought to the zero state asymptotically by applying the ...
The function r is called the stability function. [31] It follows from the formula that r is the quotient of two polynomials of degree s if the method has s stages. Explicit methods have a strictly lower triangular matrix A, which implies that det(I − zA) = 1 and that the stability function is a polynomial. [32]
A Lyapunov function for an autonomous dynamical system {: ˙ = ()with an equilibrium point at = is a scalar function: that is continuous, has continuous first derivatives, is strictly positive for , and for which the time derivative ˙ = is non positive (these conditions are required on some region containing the origin).
To introduce Lyapunov exponent consider a fundamental matrix () (e.g., for linearization along a stationary solution in a continuous system), the fundamental matrix is (() |) consisting of the linearly-independent solutions of the first-order approximation of the system.
In mathematics, in the theory of differential equations and dynamical systems, a particular stationary or quasistationary solution to a nonlinear system is called linearly unstable if the linearization of the equation at this solution has the form / =, where r is the perturbation to the steady state, A is a linear operator whose spectrum contains eigenvalues with positive real part.