Combined model approximation techniques and multiparametric programming for explicit nonlinear model predictive control Academic Article uri icon


  • This work presents a methodology to derive explicit multiparametric controllers for nonlinear systems, combining model approximation techniques and multiparametric model predictive control (mp-MPC) algorithms. Particular emphasis is given to an approach that applies a nonlinear model reduction technique, based on balancing of empirical gramians, which generates a reduced order model suitable for nonlinear mp-MPC algorithms. This approach is compared with a recently proposed method that uses a meta-modelling based model approximation technique which can be directly combined with standard multiparametric programming algorithms. The methodology is illustrated for two nonlinear models, of a distillation column and a train of CSTRs, respectively. 2012.

published proceedings


author list (cited authors)

  • Rivotti, P., Lambert, R., & Pistikopoulos, E. N.

citation count

  • 34

complete list of authors

  • Rivotti, Pedro||Lambert, Romain SC||Pistikopoulos, Efstratios N

publication date

  • July 2012