This brief concerns model and noise design relevant to drag-free and attitude control of the European satellite gravity field and steady-state ocean circulation explorer (GOCE) under different control modes. As the model must include accurate dynamics of disturbance and measurement drifts to be rejected/estimated, noise design aims to select, and to mark with the Boolean variables of the control modes, the necessary and sufficient feedback channels (noise estimator) connecting model error to noise, which are the paths through which model state variables can be updated in real-time. Noise design is applied to a generic model encompassing position and attitude control, fed by position, rate, attitude, and acceleration sensors. The resulting closed-loop becomes a state predictor, providing controllable and disturbance states to drag-free and attitude control law, switching smoothly from mode to mode. Noise estimator gains are tuned to robust performance and stability by properly assigning closed-loop eigenvalues. Tuning details and simulated results illustrating the different modes are provided.

A revision of the dynamic equations on which the UVa/Padova Type 1 diabetes metabolic simulator is based, is presented with special attention to the oral glucose absorption and the static glucagon secretion models. Slightly modifications are proposed and validated using the version 3.2 of the simulator and in-house versions of the dynamic equations found in literature. The emptying rate for the oral absorption model is modified taking into account the size of the meals, while a continuous state-space model of the glucagon secretion model suitable for embedded model control design is presented. The achieved overall relative model error in the plasma glucose is less than 2.5% for 10 virtual patients available in this FDA approved commercial simulator.