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Fuzzy Decoupling of Nonlinear Multiple-Input Multiple-Output Systems

Nikbakhsh, Sarah | 2009

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 39960 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Bozorgmehri, Ramin
  7. Abstract:
  8. Many processes in the real world are multiple-input multiple-output (MIMO) systems. There are often some interactions between the inputs and outputs. In the other words, every input affects on several outputs, and every output is affected by several inputs. In order to control of these systems, we usually desire to decouple the loops into multiple non-interacting SISO systems after proper pairing of manipulated and controlled variables. Loop interactions can destabilize a control system, so tuning controllers in an interacting MIMO system can be difficult. Decoupling problem has been discussed in the two domains: linear control and nonlinear control. However, both of them need an exact model of process. When we have not an exact model, we can use fuzzy decouplers. Fuzzy logic is much closer in spirit to human thinking and natural language than are traditional logical systems. Basically, it provides an effective means of capturing the approximate, inexact nature of the real world. In this project, two types of fuzzy decouplers are designed and implemented for two nonlinear 2×2 systems of chemical reactors. Genetic algorithms have been used for tuning of these fuzzy decoupling systems. It has been shown that performance of both types is better than linear decouplers
  9. Keywords:
  10. Fuzzy Logic ; Genetic Algorithm ; Multiple Input Multiple Output (MIMO)System ; Decoupling

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