Martin Schlegel

A Two-Level Strategy of Integrated Dynamic Optimization and Control of Industrial Processes—a Case Study

Abstract This paper discusses a two-level strategy integrating dynamic trajectory optimization and control for the operation of chemical processes. The benefit of an online dynamic re-optimization of operational trajectories in case of disturbances is illustrated by a case study on a semi-batch reactive distillation process producing methyl acetate.

Direct Sequential Dynamic Optimization with Automatic Switching Structure Detection

Abstract In this paper we present a novel method for the numerical solution of dynamic optimization problems. After obtaining a first solution at a coarse resolution of the control profiles with a direct sequential approach, the structure of the control profiles is analyzed for possible switching times and arcs. Subsequently, the problem is reformulated and solved as a multi-stage problem, with each stage corresponding to a potential arc. Order and resolution of the control parameterization are adapted to the type of the particular arc. With a case study we show that accurate solutions with only few degrees of freedom can be obtained.

Component-based implementation of a dynamic optimization algorithm using adaptive parameterization

Publisher Summary This chapter presents a component software technique applied to a dynamic optimization algorithm based on sequential approach. The implementation of the algorithm allows the optimization of existing models formulated in recent modeling environments without the need of model transfer or recoding. The numerical algorithm is capable of generating problem dependent, nonuniform discretization grids that might differ for each control variable. The software is used to solve an example problem of industrial relevant size. Based on the experience drawn from the example, benefits and drawbacks of this technology are discussed. As a new feature, the access of model information through a Competence Assessment, Planning, and Evaluation (CAPE)-OPEN interface has been introduced. The functionality of this approach has been proven by applying it to a large-scale problem. The heterogeneous implementation using CORBA as communication middleware appeared to be a practical approach, though there still exists a significant overhead in computation time solely caused by software-related reasons. Future improvements in this area will enable the use of such frameworks in industrial applications.

Dynamic Real-Time Optimization: From Off-Line Numerical Solution to Measurement-Based Implementation

Abstract The problem of optimizing a dynamic system under uncertainty is typically tackled using measurements. The methods widely used in the literature are based on repetitive optimization of a process model. Recently, tracking of the Necessary Conditions of Optimality (NCO tracking) has been proposed as a computationally less expensive alternative, which is based on the adaptation of a solution model using measurements. So far, the solution model, which contains information on the structure of the input profiles and the set of active constraints, has been derived manually using physical insight and intuition. In this paper, based on recent results on the numerical optimization of dynamic systems, we present a systematic and automated approach to generate a solution model. This concept provides the first step towards an entirely automated procedure for dynamic optimization under uncertainty via NCO tracking.