This paper studies self-triggering in sampled-data systems, where the next task release time and finishing time are predicted based on the sampled states. We propose a new self-triggering scheme that ensures finite-gain L_(2) stability of the resulting self-triggered feedback systems. This scheme relaxes the assumptions in [1] that the magnitude of the process noise is bounded by a linear function of the norm of the system state. We show that the sample periods generated by this scheme are always greater than a positive constant. We also provide dynamic deadlines for delays and propose a way that may enlarge predicted deadlines without breaking L_(2) stability, especially when the predicted deadlines are very short. Simulations show that the sample periods generated by this scheme are longer than those generated by the schemes in [1]. We also show that the predicted deadlines can be extended by our scheme. Moreover, this scheme appears to be robust to the external disturbances.
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