Lyapunov stability is weak in that it does not even imply that
converges to as approaches infinity. The states are only
required to hover around . Convergence requires a stronger
notion called *asymptotic stability*. A point is an *asymptotically stable* equilibrium point of if:

- It is a Lyapunov stable equilibrium point of .
- There exists some open neighborhood of such that,
for any
, converges
^{15.2}to as approaches infinity.

Asymptotic stability appears to be a reasonable requirement, but it does not imply anything about how long it takes to converge. If is asymptotically stable and there exist some and such that

(15.2) |

then is also called

For use in motion planning applications, even exponential convergence may not seem strong enough. This issue was discussed in Section 8.4.1. For example, in practice, one usually prefers to reach in finite time, as opposed to only being ``reached'' in the limit. There are two common fixes. One is to allow asymptotic stability and declare the goal to be reached if the state arrives in some small, predetermined ball around . In this case, the enlarged goal will always be reached in finite time if is asymptotically stable. The other fix is to require a stronger form of stability in which must be exactly reached in finite time. To enable this, however, discontinuous vector fields such as the inward flow of Figure 8.5b must be used. Most control theorists are appalled by this because infinite energy is usually required to execute such trajectories. On the other hand, discontinuous vector fields may be a suitable representation in some applications, as mentioned in Chapter 8. Note that without feedback this issue does not seem as important. The state trajectories designed in much of Chapter 14 were expected to reach the goal in finite time. Without feedback there was no surrounding vector field that was expected to maintain continuity or smoothness properties. Section 15.1.3 introduces controllability, which is based on actually arriving at the goal in finite time, but it is also based on the existence of one trajectory for a given system , as opposed to a family of trajectories for a given vector field .

Steven M LaValle 2012-04-20