Inferential adaptive control for non-uniformly sampled-data systems

An inferential adaptive control algorithm is developed for a class of non-uniformly sampled-data systems with fast and non-uniformly updated inputs and infrequently sampled outputs. The specific approach involves three steps: first, to derive the mathematical relationships between the transfer function model of the measurable output and that of the non-uniform missing outputs; second, to compute the models of the non-uniform missing outputs based on the derived mathematical relationships and the identified model of the measurable output; third, using the computed models to estimate the non-uniform missing outputs and further supply which for feedback control. The proposed control algorithm can generate fast rate control signals and has the property of minimum variance. An example is included and the simulation results illustrate the effectiveness of the proposed inferential control scheme.