Alteration in the pathological behaviour of cervical cancer

Abstract

For the first time, a distributed output feedback control scheme is presented which combines distributed model predictive control with distributed moving horizon estimation. More specifically, we combine the iterative methods of sensitivity-driven distributed model predictive control (S-DMPC) with sensitivity-driven partition-based moving horizon estimation (S-PMHE). To that end, S-PMHE is extended such that it can handle inputs of S-DMPC. The resulting distributed output feedback scheme is then applied to an alkylation benchmark process from the literature. We find that its control performance is comparable to that of fully centralized MPC and MHE but our distributed output feedback scheme is faster.