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Intelligent Control of a Biodiesel Reactor

Vasli, Navid | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54698 (06)
  4. University: Sharif University of Technology
  5. Department: Chemical and Petroleum Engineering
  6. Advisor(s): Shahrikhi, Mohammad; Vafa, Ehsan
  7. Abstract:
  8. Nowadays, due to increasing attention to produce a wide range of fuels through bioprocesses, in the present work, simulation and control of a continuous reactor to produce biodiesel from food-wastes has been addressed. In this regard, the transesterification reaction of triglyceride (a mixture of 10% (wt) Jatropha oil and 90% (wt) of edible oil residue) with methanol (6:1 molar ratio of methanol to oil) in the presence of 1% (wt) potassium hydroxide catalyst in a continuous stirred tank reactor has been simulated. For the control purposes, the bioreactor temperature and the product concentration have been controlled by manipulating heat duty and reactant feed flow rate, respectively. An intelligent adaptive controller based on neural network concept has been applied in two modes of single input-single output and multi input-multi output. At First, the neural network controller was trained offline. But, due to the presence of offset in the response of the closed-loop control system, an online version of gradient descent method has been used to update the weights of neural network. The performance of the controller has been evaluated in three different scenarios: set point tracking (±10% change in product concentration and reactor temperature), load rejection (±20% change in mass flow rate and temperature of the reactor feed) and model mismatch (±5% uncertainty in one of the reaction’s activation energies). The simulation results show that the proposed control strategy has an acceptable performance in all of these scenarios.
    Keywords
  9. Keywords:
  10. Model Mismatch ; Uncertainty ; Ester Exchange Reaction ; Biodiesel Production ; Reactor Simulation ; Control ; Adaptive Neuro Controller

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