Advanced techniques for robust dynamic optimization of chemical reactors

This thesis will focus on the application of optimal control theory to (bio-)chemical processes, where it can be applied to shift towards more sustainable production routes. It should be stressed, however, that the solution of highly non-linear systems, as those involved in (bio-)chemical processes, is not always easy to obtain and that it can lead to computational problems. Two variations of optimal control will also be analised, namely robust optimal control and multi-objective optimal control, which deal respectively with uncertain parameters and multiple objectives. These two features can be combined in a robust multi-objective optimal control problem, which will also be investigated. Two mathematical formulations to solve robust optimal control problems, the linear and sigma points approximations, will be exploited for the solution of different case studies for a number of uncertain parameters varying from one to four. The obtained results are compared and the sigma points will prove itself to be more effective than the linear approximation when dealing with highly non-linear systems. Generally, the sigma points approximation will also require lower computational time. The application of such approximations introduces an additional safety margin to account for uncertainties. Nevertheless, a loss in terms of performances is to be expected for both approaches. The multi-objective optimisation of a Siemens reactor will be faced. The results will present a clear trade-off between the production and the energy consumption and multiple optimal solutions will be found. This last problem is also solved when two uncertain parameters are present in the model equations. Despite the higher complexity of the system treated, and the high amount of solutions demanded, the sigma points will prove once more its efficiency in terms of computational time. All the results shown suggest that optimal control should be regarded at as an interesting field for additional research in the frame-works of sustainable development and sustainable production models for the (bio-)chemical industry.