Minimum variance in fast, slow and dual‐rate control loops

In certain industrial applications, the control updating rate is faster than the output sampling rate by a certain factor, which leads to dual‐rate (DR) control problems. Generally speaking, a DR controller performs better than a slow single rate (SSR) controller but worse than a fast single rate (FSR) controller in the sense of minimum variance control. This conjecture is theoretically justified in this paper for a continuous linear time‐invariant (LTI) single‐input single‐output (SISO) system. The optimal FSR, DR and SSR controllers are designed under the same performance criterion: variance of the fast sampled output. The discretization of continuous stochastic disturbance models is investigated preserving certain basic statistical properties. A linear matrix inequality (LMI) approach is developed to calculate the optimal controllers for DR and SSR loops. The theoretical results are illustrated by two simulation examples.