Time-invariant, Databased Modeling and Control of Batch Processes

Abstract

Batch reactors are often used to produce high quality products because any batch that does not meet quality speci cations can be easily discarded. However, for high-value products, even a few wasted batches constitute substantial economic loss. Fortunately, databases of historical data that can be exploited to improve operation are often readily available. Motivated by these considerations, this thesis addresses the problem of direct, data-based quality control for batch processes. Speci cally, two novel datadriven modeling and control strategies are proposed. The rst approach addresses the quality modeling problem in two steps. To begin, a partial least squares (PLS) model is developed to relate complete batch trajectories to resulting batch qualities. Next, the so called missing-data problem, encountered when using PLS models partway through a batch, is addressed using a data-driven, multiple-model dynamic modeling approach relating candidate input trajectories to future output behavior. The resulting overall model provides a causal link between inputs and quality and is used in a model predictive control scheme for direct quality control. Simulation results for two di erent polymerization reactors are presented that demonstrate the e cacy of the approach. The second strategy presented in this thesis is a state-space motivated, timeinvariant quality modeling and control approach. In this work, subspace identi cation methods are adapted for use with transient batch data allowing state-space dynamic models to be identifi ed from historical data. Next, the identifi ed states are related through an additional model to batch quality. The result is a causal, time-independent model that relates inputs to product quality. This model is applied in a shrinking horizon model predictive control scheme. Signi cantly, inclusion of batch duration as a control decision variable is permitted because of the time-invariant model. Simulation results for a polymerization reactor demonstrate the superior capability and performance of the proposed approach.