IChemE Mini Symposium
Venue: Conference Room 2, Riddel Hall, Stranmillis Road, Queen's University Belfast
Time: Wednesday, 31st August, 10:30 - 12:30
Note that InstMC and IChemE symposia have been merged.
Chair: Dr Ognjen Marjanovic
The University of Manchester
List of Talks:
Applications of Process Control to the Optimization of Pharmaceutical Processes
Prof Brian Glennon
Abstract: In this talk, the use of process control as part of a process design and optimisation strategy for pharmaceutical manufacturing processes will be discussed. The integration of PAT into the control strategy to deliver optimized process performance in a short time-frame will be reviewed. The presentation will be illustrated with several case-studies. Some on-going challenges will also be discussed.
Trajectory Tracking Control of Batch Product Quality Using Intermittent Measurements and Moving Window Estimation
Dr Ognjen Marjanovic (University of Manchester)
Abstract: In order to meet tight product quality specifications for chemical batch processes, it is vital to monitor and control product quality throughout the batch duration. However, the frequent lack of in situ sensors for continuous monitoring of product quality complicates the control problem and calls for novel control approaches. This talk will focus on the development of a new approach to realise trajectory tracking control of batch product quality in those situations where only intermittent measurements are available. The scope of this methodology consists of: 1) the identification of a partial least squares (PLS) model that works as an estimator of product quality, 2) the transformation of the PLS model into a recursive formulation utilising a moving window technique, and 3) the incorporation of the recursive PLS model as a predictor into a standard MPC framework for tracking the desired trajectory of batch product quality. The benefits of the proposed modelling and control methods are demonstrated using a simulated fermentation batch process.
Real-Time Optimization of Compressor Load Sharing
Prof Nina Thornhill (Imperial College London)
Abstract: Mathematical models for optimization may be derived from first principles or derived from measurements (data-driven models). The talk will describe a framework for optimal sharing of the workload between the parallel compressors of a compressor station in order to minimize energy consumption, where the models are based on operating data. Although data-driven models offer benefits for on-line applications, there are some challenges related to their development in a practical industrial implementation. This talk discusses building of data-driven models and demonstrates the effects of these types of models on the optimization results.