|Process intensification (PI) aims to significant improvement of process efficiency by implementing novel principles to process design. Additional benefits could be achieved by advancing the operation and the control of intensified processes. An innovative approach, which implies actuation enhancement and full integration of process design, operation and control, will be investigated in this project.
In comparison to conventional processes, intensified processes have specific dynamic and operating characteristics. These are elevated barriers for operation and control, which are examined and illustrated by means of examples in the project. Moreover, realization of modern model-based control of PI systems faces technical challenges, at the first place a lack of accurate and reliable mathematical models for novel processes, as well as those related also to the classical processes systems: non-efficient model reducing algorithms and realization of a non-linear model predictive control system. These issues are reviewed in the project in detail.
Traditionally, process synthesis consists of three consecutive phases as presented in Figure 1. Although this concept is well established in practice, it does not allow the interaction of design and control and therefore it is usually suboptimal from both economic and control standpoint. A new integral approach, based on dynamic optimization, is developed and studied by means of the industrially relevant examples. In the first stage of the new concept (Figure 2), the integral approach provides both optimal process design and optimal operation. In second phase, controllability analysis for the optimal solution is performed, while the third stage implies control design. This concept includes various process intensification methods and examines possible actuation enhancements like: spatial actuation for distributed systems (e.g. for microreactors), the use of alternative driving forces for actuation (e.g. microwaves for optimal temperature profiles), time-varying actuation of feeding or unsteady state operation, etc.
Figure 1. Traditional process synthesis Figure 2. New optimization-based process synthesis