Iterative Algorithms for Multilayer Optimizing ControlThe book presents basic structures, concepts and algorithms in the area of multilayer optimizing control of industrial systems, as well as the results of the research that was carried out by the authors over the last two decades. The methodologies and control algorithms are thoroughly illustrated by numerous simulation examples. Also, the applications to several case study examples are presented. These include ethylene distillation column, vaporizer pilot scale plant, styrene distillation line consisting of three columns and industrial furnace pilot scale plant. A temporal decomposition is applied to the Integrated Wastewater System case study to derive multilayer dynamic optimizing controller with repetitive robust model predictive control mechanism distributed over the layers operating in different time scales.Sample Chapter(s) |
Contents
Multilayer Control | 1 |
Optimizing Control Layer | 37 |
Iterative Correction with Disturbance Estimation | 73 |
Integrated System Optimization and Parameter | 81 |
ISOPE for Problems with Output Constraints | 131 |
Iterative Algorithms for Dynamic Optimizing | 183 |
furnace | 202 |
Other editions - View all
Iterative Algorithms For Multilayer Optimizing Control Mietek A Brdys,Piotr Tatjewski Limited preview - 2005 |
Iterative Algorithms for Multilayer Optimizing Control Mietek A. Brdys,Piotr Tatjewski Limited preview - 2005 |
Common terms and phrases
achieved active additional applied approach approximation assumed assumptions basic batch Brdys calculated changes Chapter complex considered constraints continuous control algorithms control inputs control layer control structure convergence convex coordination corresponding defined denote dependent derivative described direct disturbances double-loop dynamic efficient equal equations errors example formulation furnace given Hence important inner loop input-output inputs interconnected ISOPE algorithm iterations lead linear load mapping matrix measurements method minimize MMOP modified multipliers necessary needed nonlinear obtained operating optimization problem optimizing control outer loop output output constraints parameter estimation performance function plant possible practical predicted presented process outputs reason relaxation respectively satisfied set-point shown simulation solution solving steady-state Step strategy structure subsystem sufficiently task temperature term Theorem tion trajectories true uncertainty usually values variables vector yields zone