In this paper we consider Lévy processes without negative jumps,
reflected at the origin. Feedback information about the level of
the Lévy process (`workload level') may lead to adaptation of
the Lévy exponent. Examples of such models are queueing models
in which the service speed or customer arrival rate changes
depending on the workload level, and dam models in which the
release rate depends on the buffer content. We first consider a
class of models where information about the workload level is
continuously available. In particular, we consider dam processes
with a two-step release rule and M/G/1 queues in which the arrival
rate, service speed, and/or jump size distribution may be adapted
depending on whether the workload is above or below some level
K. Secondly, we consider a class of models in which the
workload can only be observed at Poisson instants. At these
Poisson instants, the Lévy exponent may be adapted based on the
amount of work present. For both classes of models, we determine
the steady-state workload distribution.
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