Hong-Gui Han, Shi-Jia Fu, Hao-Yuan Sun, Chen-Yang Wang
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Robust Model Free Adaptive Predictive Control for Wastewater Treatment Process With Packet Dropouts.
External disturbances and packet dropouts will lead to poor control performance for the wastewater treatment process (WWTP). To address this issue, a robust model-free adaptive predictive control (RMFAPC) strategy with a packet dropout compensation mechanism (PDCM) is proposed for WWTP. First, a dynamic linearization approach (DLA), relying only on perturbed process data, is employed to approximate the system dynamics. Second, a predictive control strategy is introduced to avoid a short-sighted control decision, and an extended state observer (ESO) is used to attenuate the disturbance effectively. Furthermore, a PDCM strategy is designed to handle the packet dropout problem, and the stability of RMFAPC is rigorously analyzed. Finally, the correctness and effectiveness of RMFAPC are verified through extensive simulations. The simulation results indicate that RMFAPC can significantly reduce IAE by 0.0223 and 0.1976 in two scenarios, regardless of whether the expected value remains constant or varies. This comparison to MFAPC demonstrates the superior robustness of RMFAPC against disturbances. The ablation experiment on PDCM further confirms its capability in handling the packet dropout problem.
期刊介绍:
The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.