Closed physical systems eventually come to rest, the reason being that due to friction of some kind they continuously lose energy. The mathematical exten- sion of this principle is the concept of a Lyapunov function. A Lyapunov function for a dynamical system, of which the dynamics are modelled by an ordinary differential equation (ODE), is a function that is decreasing along any trajectory of the system and with exactly one local minimum. This implies that the system must eventu- ally come to rest at this minimum. Although it has been known for over 50 years that the asymptotic stability of an ODE's equilibrium is equivalent to the existence of a Lyapunov function for the ODE, there has been no constructive method for non-local Lyapunov functions, except in special cases. Recently, a novel method to construct Lyapunov functions for ODEs via linear programming was presented (5), (6), which includes an algorithmic description of how to derive a linear program for a continuous autonomous ODE, such that a Lyapunov function can be constructed from any feasible solution of this linear program. We will show how to choose the free parameters of this linear program, dependent on the ODE in question, so that it will have a feasible solution if the equilibrium at the origin is exponentially sta- ble. This leads to the first constructive converse Lyapunov theorem in the theory of dynamical systems/ODEs.
[1]
S. Sastry.
Nonlinear Systems: Analysis, Stability, and Control
,
1999
.
[2]
A. M. Lyapunov.
The general problem of the stability of motion
,
1992
.
[3]
A. Vicino,et al.
On the estimation of asymptotic stability regions: State of the art and new proposals
,
1985
.
[4]
Yinyu Ye,et al.
Interior point algorithms: theory and analysis
,
1997
.
[5]
Alexander Schrijver,et al.
Theory of linear and integer programming
,
1986,
Wiley-Interscience series in discrete mathematics and optimization.
[6]
A. Fuller,et al.
Stability of Motion
,
1976,
IEEE Transactions on Systems, Man, and Cybernetics.
[7]
Sigurður F. Marinósson,et al.
Lyapunov function construction for ordinary differential equations with linear programming
,
2002
.
[8]
Austin Blaquière,et al.
Nonlinear System Analysis
,
1966
.