Performance Comparison of Predictive Controllers in Optimal and Stable Operation of Wastewater Treatment Plants

Authors

  • A. R. Kosari Department of Aerospace, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran
  • A. Torabian School of Environment, College of Engineering, University of Tehran, Tehran, Iran
  • B. Aminzadeh School of Environment, College of Engineering, University of Tehran, Tehran, Iran
  • H. Hasanlou School of Environment, College of Engineering, University of Tehran, Tehran, Iran
  • N. Mehrdadi School of Environment, College of Engineering, University of Tehran, Tehran, Iran
Abstract:

Any proper operation could be translated as a constrained optimization problem inside a WWTP, whose nonlinear behavior renders its control problems quite attractive for performance of multivariable optimization–based control technique algorithms, such as NMPC. The main advantage of this control technique lies in its ability to handle model nonlinearity as well as various types of constraints on the actuators and state variables. The current study presents the process of BSM1 building, step by step, proposing appropriate numerical methods are creating the simulation model in MATLAB environment. It also makes a detailed comparison of the proposed NMPC with five recent predictive control schemes, namely LMPC, hierarchical MPC+ff, EMPC, and MPC+fuzzy, along with the default PI. The performance of predictive control schemes is much better than the default PI; however, something of highest importance is the ability to use the proposed control scheme in real systems, for a real application faces several limitations, especially in terms of the equipment. Finally, in order to compare predictive controllers, it is necessary to determine the same conditions so that results from more days can be used, and, if needed, more than 28 days have to be simulated. MOI index can help determine which of the proposed control scheme is really applicable.

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Journal title

volume 5  issue 4

pages  821- 838

publication date 2019-10-01

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