Jan Busch

A framework for the mixed integer dynamic optimisation of waste water treatment plants using scenario-dependent optimal control

Abstract In many real life processes, operational objectives, constraints and the process itself may change over time. This is due to changing product requirements, market demands and other external or internal influences, which constitute a certain scenario. Model-based techniques can provide optimal solutions to the corresponding scheduling and process control problems. This paper focuses on those situations, where the objectives and constraints of plant operation depend on the scenario and therefore change over time. A framework is developed, which enables the modelling and scheduling of different operational strategies on the optimisation horizon. A case study involving a waste water treatment plant is used to demonstrate the approach. Existing expert knowledge is used to relate certain operational objectives and constraints to corresponding scenarios. It is shown that easily interpretable optimisation results are obtained. Also, the results are significantly improved as compared to a weighted average approach only approximating sequential strategies.

Integration of model-predictive scheduling, dynamic real-time optimization and output tracking for a wastewater treatment process

Abstract A hierarchical control architecture for the integration of scheduling decisions, dynamic real-time optimization and tracking control is proposed. It is shown how the discrete-continuous problem of simultaneous scheduling and trajectory optimization on a receding horizon can be integrated within the upper control layer of a two-layer architecture. On the upper layer, the optimal plant strategy defined by a sequence of control objectives and optimal control moves is computed on a long time horizon. The lower control layer consists of a state observer and a fast-acting tracking controller which operates on a short time horizon. The properties of this architecture are illustrated by a case study in which a wastewater treatment plant is operated under the influence of external disturbances. Conflicting operational objectives may be valid, depending on the state of the plant and the expected disturbances. By calculating an optimal sequence of operational strategies and control moves on the receding horizon, economically optimal operation of the plant can be achieved.

RUN-TO-RUN CONTROL OF MEMBRANE FILTRATION PROCESSES

Abstract Membrane filtration processes are often operated cyclically, where one cycle comprises a filtration and a backwashing phase. Due to the complex mechanisms involved, these filtration processes are mostly operated with fixed values of the manipulated variables. In this paper, a model-based process control approach is introduced, which is based upon run-to-run control theory. To evaluate the controller, a suitable model of submerged membrane filtration in wastewater applications is developed, which describes the main process phenomena while being computationally inexpensive. The model-based controller is then tested in a simulation environment employing a validated reference model. Excellent results with respect to prediction quality and optimality are obtained.