Today's processes are becoming more integrated in order to reduce energy consumption, to increase raw materials utilization, and to reduce environmental effects of effluents. All of these developments have made the control of processes increasingly difficult and have driven the process industry's need for improved control techniques.
Improved control leads to savings in resources, improved safety, and reduced pollution.
It is the goal of our research to develop practical techniques for control and design of industrial processes. Robust Control of Constrained Systems Models are only approximate descriptions of physical reality. Although theory for handling model uncertainty is well developed for control of linear systems without constraints, its impact on practice has been minimal. For example, compressors have finite throughput, and distillation columns have weeping and flooding limits. The goal for this work is to develop practical tools to design controllers for systems with operating constraints and model uncertainty such that performance is optimized.