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作者:

Chen, Cong (Chen, Cong.) | Sun, Haoyuan (Sun, Haoyuan.) | Han, Honggui (Han, Honggui.)

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EI Scopus

摘要:

Model predictive control is an effective way to achieve the control of wastewater treatment process (WWTP). However, it is a challenge to control multiple objectives due to the complexity of WWTP. To solve this problem, an eigenvector based multiobjective model predictive control (EMMPC) strategy is developed for WWTP to handle the conflicting objectives. First, a multiobjective control scheme is designed with adaptive fuzzy neural network prediction (AFNNP) model and gradient eigenvector optimization (GEO) algorithm. Then, AFNNP can be used to describe the nonlinear of WWTP to predict the controlled variables. Second, GEO is presented to obtain the control laws of the multiple control objectives. Specifically, GEO can reduce the computational burden by avoiding the determination of the control objective weights. Third, the stability of EMMPC is provided in theory. Finally, EMMPC is implemented on the benchmark simulation platform to demonstrate the effectiveness of the presented multiobjective control method. © 2023 IEEE.

关键词:

Multiobjective optimization Eigenvalues and eigenfunctions Simulation platform Reclamation Model predictive control Orbits Forecasting Fuzzy neural networks Fuzzy inference Wastewater treatment Adaptive control systems

作者机构:

  • [ 1 ] [Chen, Cong]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 2 ] [Sun, Haoyuan]Beijing University of Technology, Faculty of Information Technology, Beijing, China
  • [ 3 ] [Han, Honggui]Beijing University of Technology, Faculty of Information Technology, Beijing, China

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年份: 2023

页码: 12-17

语种: 英文

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SCOPUS被引频次: 1

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