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— This paper presents a robust nonlinear model pre-dictive control scheme and its application to a batch bioreactor. The approach is based on the description of the uncertainty evolution as a scenario tree. This makes it possible to take explicitly into account the future disturbances and control inputs leading to a non-conservative approach that is not(More)
This paper studies the reduction of the conservativeness of robust nonlinear model predictive control (NMPC) via the reduction of the uncertainty range using guaranteed parameter estimation. Optimal dynamic experiment design is formulated in the framework of robust NMPC in order to obtain probing inputs that maximize the information content of the feedback(More)
In the last years many research studies have presented simulation or experimental results using Nonlinear Model Predictive Control (NMPC). The computation times needed for the solution of the resulting nonlinear optimization problems are in many cases no longer an obstacle due to the advances in algorithms and computational power. However, NMPC is not yet(More)