title: Generalized predictive control for non-uniformly sampled systems
abstract: In this paper, we study digital control systems with non-uniform updating and sampling patterns, which include multirate sampled-data systems as special cases. We derive lifted models in the state-space domain. The main obstacle for generalized predictive control (GPC) design using the lifted models is the so-called causality constraint. Taking into account this design constraint, we propose a new GPC algorithm, which results in optimal causal control laws for the non-uniformly sampled systems. The solution applies immediately to multirate sampled-data systems where rates are integer multiples of some base period
keyphrases: digital control systems multirate sampled-data systems GPC causality constraint optimal causal control laws integer multiples generalized predictive control design nonuniformly sampled systems nonuniform updating patterns nonuniform sampling patterns state-space models