A data-driven subspace design for dual-rate predictive control

A class of dual-rate system with a fast control updating rate and a slow output sampling rate is considered. Lifting technology is applied to derive lifted state space model and a subspace equation for dual-rate systems. From the subspace equation, the dual-rate predictive control law is calculated from a set of input/output (I/O) open-loop experimental data and, thus, this approach is data-driven since it does not involve an explicit model. The outputs of dual-rate system have good tracking performance .The simulation result shows that the proposed method is effective.