Resource-aware switching design with self-triggered sampling: a candidate-based switching framework

This paper addresses the resource-aware switching design problem of switched systems via self-triggered sampling, with a focus on reducing a combined cost associated with both sampling and switching. A more flexible self-triggered strategy is constructed by introducing an adjustable parameter to enhance design freedom beyond existing switching approaches. Based on the sampled data, we propose a novel candidate-based switching framework that includes a switching candidate mechanism and a switching decision mechanism to determine the desired switching update. By employing an average energy cost metric, this candidate-based switching law effectively reduces the combined cost of sampling and switching. Furthermore, the developed framework avoids Zeno behavior in both sampling and switching processes, and ensures the exponential stability of the resulting closed-loop system. Finally, the effectiveness and advantages of the proposed switching law are demonstrated through extensive simulation results. © 2026 IEEE.