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Fuzzy Neural Network-Based Data-Driven Robust Model Predictive Control for Wastewater Treatment Processes Under
IEEE Transactions on Cybernetics
|April 13, 2026
Summary
This study introduces a data-driven robust model predictive control (DRMPC) to stabilize wastewater treatment plants (WWTPs) facing data loss and sensor faults. The DRMPC ensures reliable control despite communication constraints and external disturbances.
Area of Science:
- Environmental Engineering
- Control Systems Engineering
- Data-Driven Modeling
Background:
- Wastewater treatment processes (WWTPs) rely on wireless networks for data transmission, but face challenges like data packet losses due to limited bandwidth.
- Intermittent sensor faults, caused by sludge adhesion and aging, lead to probabilistic sampling (PS), further degrading control performance and system stability.
Purpose of the Study:
- To propose a data-driven robust model predictive control (DRMPC) approach for stabilizing WWTPs under communication constraints and external disturbances.
- To develop a control strategy that addresses probabilistic sampling and consecutive packet losses in WWTP data transmission.
Main Methods:
- An equivalent probabilistic sampling (EPS) model was established to characterize data randomness from communication constraints.
- A two-loop control framework was designed, featuring a nominal model predictive control (MPC) with a multistep identifier and a fuzzy neural network (FNN) controller.
- The cost function was formulated to enhance tracking control by incorporating predictive outputs and control error variation.
Main Results:
- The proposed DRMPC effectively stabilizes WWTPs despite communication limitations and external disturbances.
- The FNN controller successfully mitigated the impact of external disturbances, ensuring actual output convergence to the nominal output.
- Theoretical stability analysis was provided, and experimental validation on the Benchmark Simulation Model No.1 (BSM1) confirmed the approach's effectiveness.
Conclusions:
- The DRMPC approach offers a robust solution for controlling WWTPs under challenging communication environments.
- The integrated control framework enhances system stability and performance, addressing data loss and sensor fault issues.
- This data-driven strategy provides a reliable method for maintaining WWTP operational integrity.
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