… We use multi-stage NMPC with orthogonal collocation on finite elements to solve problem
(7… Morari, “Approximating explicit model predictive control using constrained neural networks,” …

… explicit ML-MPC framework for nonlinear processes using multi-parametric programming.
Specifically, a self-adaptive approximation … and the Jacobians of constraints. However, since it …

… GP model used to approximate plant-model mismatch, the bounded disturbance assumption
is no longer satisfied by the support W = R n w . Instead of trying to enforce constraints for …

… systems with nonlinearities and constraints, it suffers from high … an approximate two-loop
nonlinear model predictive control (… The proposed approximation method utilizes orthogonal …

… The MPC framework used for this work considers a discrete-time linear state space system
… ‘‘Approximate explicit constrained linear model predictive control via orthogonal search tree,…

… , “Approximate explicit constrained linear model predictive control via orthogonal search tree,…
Fikar, “Complexity reduction of explicit model predictive control via separation,” Automatica, …

… with a linear or quadratic cost function can be explicitly computed … constraints limiting the
deployment of explicit solutions to relatively small MPC problems, and motivating approximate …

… to define the approximate explicit piecewise linear state feedback through applying the
orthogonal search tree structure on the partition. The solution of the constrained linear MPC …

… Model Predictive Control (MPC) is an optimal control method treating … Grancharova 33
approximated explicit constrained linear model predictive control via orthogonal search tree. By …

… method that treats constraints in an efficient way [11]. It has the advantages of … [20] impose
an orthogonal search tree structure on the partition to determine an approximate explicit PWA …