Dynamic Scheduling and Control-Quality Optimization of Self-Triggered Control Applications

In English Time-triggered periodic control implementations are over provisioned for many execution
scenarios in which the states of the controlled plants
are close to equilibrium. To address this inefficient use
of computation resources, researchers have proposed
self-triggered control approaches in which the control
task computes its execution deadline at runtime
based on the state and dynamical properties of the
controlled plant. The potential advantages of this control
approach cannot, however, be achieved without
adequate online resource-management policies. This
paper addresses scheduling of multiple self-triggered
control tasks that execute on a uniprocessor platform,
where the optimization objective is to find tradeoffs
between the control performance and CPU usage
of all control tasks. Our experimental results show
that efficiency in terms of control performance and
reduced CPU usage can be achieved with the heuristic
proposed in this paper.