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Optimal Control of Chemical Reactors Based on Optimization Methods Inspired from Artificial Immune Systems

Mohammadi, Mohammad | 2010

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 40524 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Pishvaie, Mahmoud Reza
  7. Abstract:
  8. Artificial immune systems (AIS) constitute a novel area of bio-inspired computing. Biological models of the natural immune system, in particular the theories of clonal selection, immune networks and negative selection, have provided the inspiration for AIS algorithms. Moreover, such algorithms have been successfully employed in a wide variety of different areas, but have not been applied for chemical processes yet. One important part of the immune systems is lymphatic system. Clonal selection is one of the few algorithms that belong to the family of AIS techniques. Clonal selection algorithm is the computational implementation of the clonal selection principle. In this project, we have provided some novel algorithms for optimization inspired from distribution and function of lymphatic system and clonal selection principle. Moreover, these algorithms applied to several static and dynamic optimization problems. For optimal control problems, we have applied these algorithms to the two different approaches of the dynamic optimization. The first approach is based on Discretized Control Vector (DCV) that employs the evolutionary algorithms to obtain the best solution for discretized control action in dynamic optimization problem. The second approach is called Control Vector Parameterization (CVP). In this approach, control action is generated in feedback form, i.e., a set of trial functions of state variables are expanded by multiplying with some unknown coefficients. At last, several case studies including chemical reactors and bioreactors have been solved by these approaches
  9. Keywords:
  10. Optimal Control ; Chemical Reactors ; Artificial Immune System (AIS) ; Lymphatic System

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