On Popov-type stability criteria for neural networks.
Let be a general control system; the existence of a smooth control-Lyapunov function does not imply the existence of a continuous stabilizing feedback. However, we show that it allows us to design a stabilizing feedback in the Krasovskii (or Filippov) sense. Moreover, we recall a definition of a control-Lyapunov function in the case of a nonsmooth function; it is based on Clarke’s generalized gradient. Finally, with an inedite proof we prove that the existence of this type of control-Lyapunov...
Let be a general control system; the existence of a smooth control-Lyapunov function does not imply the existence of a continuous stabilizing feedback. However, we show that it allows us to design a stabilizing feedback in the Krasovskii (or Filippov) sense. Moreover, we recall a definition of a control-Lyapunov function in the case of a nonsmooth function; it is based on Clarke's generalized gradient. Finally, with an inedite proof we prove that the existence of this type of control-Lyapunov...
We consider a finite-dimensional control system , such that there exists a feedback stabilizer that renders globally asymptotically stable. Moreover, for with an output map and , we assume that there exists a -function such that , where is the maximal solution of , corresponding to and to the initial condition . Then, the gain function of given byis well-defined. We call profile of for any -function which is of the same order of magnitude as . For the double integrator...
We consider a finite-dimensional control system , such that there exists a feedback stabilizer k that renders globally asymptotically stable. Moreover, for (H,p,q) with H an output map and , we assume that there exists a -function α such that , where xu is the maximal solution of , corresponding to u and to the initial condition x(0)=0. Then, the gain function of (H,p,q) given by 14.5cm is well-defined. We call profile of k for (H,p,q) any -function which is of the same order of...