Nonlinear model predictive control: Issues and applications (Q2776227)

A selection of main open issues in the analysis, synthesis, and application of nonlinear model predictive control (NMPC) are examined. The nonlinear model structure, computational efficiency of NMPC algorithms, and the disturbance estimation procedures are emphasized. It is suggested that the modelling of distributed parameter systems could lead to more accurate nonlinear process models for the NMPC controller.NEWLINENEWLINENEWLINEOn the other hand, in the absence of any fundamental process description, the nonlinear input-output models can be successfully used. Three representative examples are included. The nonlinear moving horizon estimation procedure for systems with incomplete information is demonstrated on the Van der Vusse reactor. The computational efficiency of an NMPC algorithm is examined on a fed-batch bioreactor. Finally an analytic solution to the 2-norm NMPC problem for SISO systems modelled by Volterra-Laguerre series is implemented on a continuous bioreactor.NEWLINENEWLINEFor the entire collection see [Zbl 0976.00019].