A COMPUTER-AIDED-DESIGN TOOL FOR ROBUSTNESS ANALYSIS AND CONTROL-RELEVANT IDENTIFICATION OF HORIZON PREDICTIVE CONTROL WITH APPLICATION TO A BINARY DISTILLATION COLUMN

This paper describes a MATLAB-based computer-aided design tool, IRA-HP C, which accomplishes integrated system identification and robustness analysis For Horizon Predictive Control (HPC), a model predictive cont rol algorithm implemented on the Application Module of the Honeywell T DC 3000 distributed control system. The tool addresses lifecycle as we ll as functional aspects of the technology, with the goal of making ad vanced control principles more accessible to the practising control en gineer. IRA-HPC systematically performs the various stages of system i dentification in a control-relevant framework (addressing input design , parameter estimation, and model validation from the standpoint of th e final purpose of the model, which is control system design), followe d by robust HPC controller tuning using the Structured Singular Value (mu) paradigm as a basis. The benefits of the tool are shown experimen tally in the modelling and control of a methanol/isopropanol pilot-sca le distillation column, interfaced to an industrial-scale real-time co mputing testbed. The example demonstrates the practical feasibility of this tool and its benefits in terms of simplifying the choices of des ign variables in integrated identification and control design.