Explicit hybrid model-predictive control: The exact solution

A multiparametric model‐based optimization and control approach to anaesthesia

“…Dua et al, [47] Oberdieck et al, [56] Axehill et al, [57] Nascu et al, [60] Trifkovic et al [61] Robust mp-MPC (the immunity of a system against perturbations)…”

“…Local linearization (described in Nascu [76] ) Piece-wise linearization leading to a piece-wise affine formulation, described in Dua et al and Oberdieck et al [47,56] Exact linearization as in Figure 6 based on a parameter scheduling technique shown in Nascu. [17] Here the inverse of the Hill curve in (6) is implemented in the controller with the nominal patient model parameters in Table 3-as shown in Figure 6.…”

Convex Lifting: Theory and Control Applications

“…Explicit model predictive control (MPC) has received significant attention in control community due to its relevance for rather small-dimensional systems [10], [17], [36], [37], [41]. However, even if the controllers are explicitly obtained, there exist major problems in terms of their implementation once the number of regions in the state-space partition becomes large.…”

Model-based multi-parametric programming strategies towards the integration of design, control and operational optimization

“…In the last decade, multi-parametric programming has received considerable attention due to its applicability to a wide range of optimization and engineering problems such as optimal control ( [34,307]), the integration of design and control (Chapter 6), multi-objective optimization ( [256,297]) and bilevel optimization ( [104,105]). This in return has led to the development of novel algorithms for several classes of multi-parametric programming problems, such as multi-parametric mixed-integer programming ( [98,255]), multi-parametric dynamic programming ( [48,295]) and even inverse multi-parametric programming ( [16,155,250]). …”