الفهرس | Only 14 pages are availabe for public view |
Abstract This thesis is mainly concerned with the design o~ an algqrithm ~or static optimization o~ dynamic industrial The idea behind theprqcesses. suggested algorithm is to represent the target syst~m by a nonlinear model relating the per~ormance index to the manipulating inputCs). Identi~ication of the model is carried out by using the Extended Kalman Fi1ter CEKF). The results o~ the identi~ication are then used to calculate the manipulatingopt.Imal values o~ the inputCs). The thesis includes a general introduction to the subject. and a bibliographic research that aims to analyze the existing static optimization methods and nonlinear ~i1tering methods. The CEKF) is chosen as a nonlinear identi~i cation algori t.hm to be used in the development o~ the optimization algorithm. This research work indicated that the developed algorithm is a new static optimization industrialmethod o~ dynamic processes. The development o~ the algorithm is then presented. The robustness o~ the suggested algorithm is then investigated via simulation study. The simulation results indicated that the algorithm is in general conver ging to the new oper ating condi tions but. under certain conditions, may.be biased. This bias is due to the identification technique. An algorithm for optimal transfer of the system 1’rom initial operating conditions to the identi fi e.d.-opti mal operating conditions is also developed. The developed static optimization algorithm is applied to optimize the operation of a distillation column existing at ”Laboratoire d’Automatique de Grenoble” (LAG) in France. The results indicated that the algorithm is capable of predicting the optimal values of inputs. |