Intermittent Redesign of Analog Controllers via the Youla Parameter
Provides a practical solution for control engineers dealing with irregular sampling in digital control systems.
The paper proposes a constructive algorithm to redesign analog stabilizing controllers for intermittent sampling, preserving closed-loop stability and achieving (sub)optimal H2 and H∞ performance under unknown sampling patterns.
The paper studies digital redesign of linear time-invariant analog controllers under intermittent sampling. The sampling pattern is only assumed to be uniformly bounded, but otherwise irregular and unknown a priori. The contribution of the paper is twofold. First, it proposes a constructive algorithm to redesign any analog stabilizing controller so that the closed-loop stability is preserved. Second, it is shown that when applied to (sub)optimal $H^2$ and $H^\infty$ controllers, the algorithm produces (sub)optimal sampled-data solutions under any a priori unknown sampling pattern. The proposed solutions are analytic, computationally simple, implementable, and transparent. Transparency pays off in showing the optimality, under a fixed sampling density, of uniform sampling for both performance measures studied.