System level disturbance reachable sets and their application to tube-based MPC

Tube-based model predictive control (MPC) methods leverage tubes to bound deviations from a nominal trajectory due uncertainties in order ensure constraint satisfaction. This paper presents novel tube?based MPC formulation based on system level disturbance reachable sets (SL?DRS), which the affine parameterization (SLP). We show that imposing finite impulse response (FIR) SLP guarantees containment of all future sequence SL?DRS. allows us formulate tube?MPC (SLTMPC) method using SL?DRS as tubes, enables concurrent optimization and while positively invariant terminal set. Finally, we can also be computed offline.