Online reference computation for feasible model predictive control

Online reference computation for feasible model predictive control is introduced. We consider N step constrained model predictive control problems. The constraint on the input is fixed. The constraint on the state is given by either a terminal state equality or a combination of sets which depend on an N step reference sequence. Assuming that the control problem at current time is feasible, we want to know the set of terminal states or new references such that the problem at the next time instant is still feasible. We first introduce the general problems and then provide the algorithms for the linear system case using reachability analysis.