New conditions for the exponential stability of nonlinear sampled-data systems
非线性采样系统指数稳定的新条件

Stability problem of nonlinear sampled-data systems is investigated. The Lyapunov theorem and its converse theorem of globally exponential stability for the discrete-time systems family in which the sampling period is a parameter are proved. New sufficient conditions that guarantee globally exponential stability of the closed-loop sampled-data systems are presented respectively for the general approximation model and the Euler approximation model. Compared with earlier results, new conditions ignore the assumption that Lyapunov functions are globally Lipschitz, and hence weaken the sufficient conditions to warrant globally exponential stability of the closed-loop systems.