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Adaptive generic model control: Dual composition control of distillation

Authors

  • K. Yamuna Rani,

    1. Simulation, Optimization and Control Group, Indian Institute of Chemical Technology, Hyderabad 500 007, India
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  • K. Gangiah

    Corresponding author
    1. Simulation, Optimization and Control Group, Indian Institute of Chemical Technology, Hyderabad 500 007, India
    • Simulation, Optimization and Control Group, Indian Institute of Chemical Technology, Hyderabad 500 007, India
    Search for more papers by this author

Abstract

Generic model control (GMC) takes care of parametric mismatch for underdamped, closed-loop specification, whereas robust generic model control (RGMC) can handle parametric mismatch for any closed-loop specification. But, neither GMC nor RGMC is capable of compensating for structural mismatch. In this study, adaptive GMC(AGMC) and adaptive RGMC (ARGMC) structures are proposed, and their effectiveness over GMC and RGMC is demonstrated with several examples. AGMC exhibits better performance over ARGMC, GMC, and RGMC in all the cases of no process/model mismatch, parametric mismatch as well as structural mismatch.

Distillation adaptive generic model control (DAGMC) structure is also proposed for dual composition control of distillation. Since embedding of distillation state-space model in the basic GMC law is practically impossible, linear and nonlinear models are proposed with adaptation using distillation process data, and DAGMC is applied to two typical nontrivial distillation units. Nonlinear DAGMC exhibited better performance over linear DAGMC.

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