Article
Automation & Control Systems
Honggui Han, Chengcheng Feng, Haoyuan Sun, Junfei Qiao
Summary: In this paper, a self-organizing fuzzy terminal sliding mode (SOFTSM) control strategy is proposed to accurately track the dissolved oxygen (DO) concentration in wastewater treatment process. The method combines terminal sliding mode controller, self-organizing fuzzy neural network, and adaptive law, and is tested on a benchmark simulation model.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Environmental
Jinkun Zhao, Hongliang Dai, Zeyu Wang, Cheng Chen, Xingwei Cai, Mengyao Song, Zechong Guo, Shuai Zhang, Xingang Wang, Hongya Geng
Summary: In this study, a self-organizing fuzzy neural network combined with predictive algorithms was used to improve the modeling and control of municipal wastewater treatment process. It could identify sewage treatment plants in real-time and provide dynamic feedback to improve water quality. The integration with model predictive control further enhanced the accuracy and efficiency of the control process. This research is of great significance for improving the efficiency of sewage treatment process.
JOURNAL OF WATER PROCESS ENGINEERING
(2023)
Article
Automation & Control Systems
Honggui Han, Hongxu Liu, Jiaming Li, Junfei Qiao
Summary: In this article, a cooperative fuzzy-neural controller is proposed for wastewater treatment process, which improves operation performance by coordinating structure and parameters. The controller demonstrates superior control precision and low computational burden through a balanced redundant structure and optimized global and local parameters coordination.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Letter
Automation & Control Systems
Peihao Du, Weimin Zhong, Xin Peng, Linlin Li, Zhi Li
Summary: This letter addresses the issue of data-driven fault compensation tracking control for a coupled wastewater treatment process (WWTP) affected by sensor faults. Invariant set theory is utilized to eliminate the conditions of coupled non-affine dynamics and explicitly express the control inputs. An adaptive fault compensation mechanism is developed to adapt to the effects of sensor faults. Experimental studies on a standardized WWTP platform are conducted to demonstrate the effectiveness of the proposed strategy.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2023)
Article
Environmental Sciences
Fei Li, Zhong Su, Gonging Wang
Summary: The optimization control scheme based on dynamic multi-objective immune system has shown effectiveness in resolving conflicting performance indicators in wastewater treatment plants (WWTPs). By dividing the control process into dynamic and tracking control layers, adapting energy consumption and effluent quality models, and utilizing an adaptive dynamic immune optimization algorithm, the method successfully optimized complex and conflicting performance indicators. The competitive advantage of this method in control effectiveness was demonstrated through evaluation on a benchmark simulation platform.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Engineering, Multidisciplinary
Han HongGul, Wang Tong, Sun HaoYuan, Wu XiaoLong, Li Wen, Qiao JunFei
Summary: A fuzzy super-twisting algorithm sliding mode controller is developed for controlling the dissolved oxygen concentration in municipal wastewater nitrification process. The controller utilizes a fuzzy neural network model to approximate the oxygen dynamics and employs a super-twisting sliding mode controller to stabilize the system and suppress the modeling error. Experimental results on wastewater treatment benchmark simulation model no. 2 (BSM2) demonstrate the advantages of the proposed method in multiple-units oxygen concentration control.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2022)
Article
Automation & Control Systems
Peihao Du, Weimin Zhong, Xin Peng, Zhongmei Li, Linlin Li
Summary: The increasing utilization of wastewater requires dedicated attention to potential security threats and the formulation of strategies for defense, response, and future protection. This article proposes an adaptive performance self-recovery control strategy for wastewater treatment processes with nonideal actuators. The strategy enhances the faulty performance self-recovery capability of the system while ensuring robust output regulation and fast convergence.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Mathematics
Ali Najem Alkawaz, Jeevan Kanesan, Irfan Anjum Badruddin, Sarfaraz Kamangar, Mohamed Hussien, Maughal Ahmed Ali Baig, N. Ameer Ahammad
Summary: This study presents two models of self-organizing map (SOM) formulated as an optimal control problem. The first model focuses on the weight updating equation of the best matching units in each iteration, while the second model considers the weight updating equation of all nodes in the SOM. The SOMOC2 model performs better by considering all nodes in the Hamiltonian equation and produces a greater improvement in terms of mean quantization error.
Article
Green & Sustainable Science & Technology
Feini Huang, Wenqing Li, Wenhao Shen, Panagiotis Seferlis, Yi Man, Jean-Pierre Corriou
Summary: Due to the high pollution loads in the papermaking industry, a large amount of greenhouse gases are emitted during the wastewater treatment process. In order to reduce these emissions, an intelligent control scheme based on dissolved oxygen control has been developed. The simulation results show that the proposed hierarchical optimal proportional-integral control scheme can effectively reduce the greenhouse gas emissions compared to the open-loop operation.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Environmental Sciences
Abdul Gaffar Sheik, V. S. Raghu Kumar Machavolu, Murali Mohan Seepana, Seshagiri Rao Ambati
Summary: By using the Supervisory and Override Control Approach in a wastewater treatment plant, better removal of organic matter and phosphorus can be achieved with a slight increase in operating costs. The application of fuzzy and PI control schemes can further improve removal efficiency, especially when So control loops are in place.
Article
Engineering, Multidisciplinary
ShengLi Du, PeiXi Chen, HongGui Han, JunFei Qiao
Summary: This article studies the dissolved oxygen (DO) concentration control problem in wastewater treatment process (WWTP). Unlike existing control strategies, a different control framework is developed. An intelligent control method of DO concentration based on reinforcement learning (RL) algorithm is presented to resolve the DO concentration control problem. By using the deep deterministic policy gradient (DDPG) algorithm, the DO concentration of the fifth tank in the activated sludge reactor can be adjusted dynamically. Additionally, by designing two different reward functions and analyzing the relationships among effluent quality, energy consumption, and DO concentration, the target of energy-saving and emission-reducing is achieved. The simulation results indicate that the designed control method can reduce energy consumption while ensuring that the effluent quality meets the specified standards.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2023)
Article
Chemistry, Multidisciplinary
Jing Zhao, Hui Hou, Qi-Yu Huang, Xun-Gao Zhong, Peng-Sheng Zheng
Summary: In this paper, a control system based on a novel neural network controller is proposed for accurately manipulating single or multiple cells using holographic optical tweezers. The system includes a main controller, a compensation controller, and a higher order sliding mode for precise cell manipulation and multi-cell cooperative control. The proposed control system outperforms other neural network controllers in terms of control performance.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Artificial Intelligence
Gongming Wang, Junfei Qiao
Summary: This article presents an efficient self-organizing fuzzy neural network (SOFNN) called IDPT-SOFNN, which is capable of extracting effective features and dynamically adjusting its structure for better learning speed, accuracy, and generalization capability. It has shown superior performance compared to existing methods in handling practical complex data.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Qili Chen, Junfang Fan, Wenbai Chen, Ancai Zhang, Guangyuan Pan
Summary: In this paper, a dimension-reducible data-driven optimization control framework for wastewater treatment process (WWTP) is proposed. The constraint relationship between control variables is approximated using a neural network, and the optimization search is performed in a low-dimensional space. The convergence of the process is ensured through mathematical analysis. Experimental simulation results show the effectiveness of this approach in achieving an optimal solution in control systems.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Marine
Ning Wang, Huihui Wu, Yuhang Zhang, Jialin Song, Yejin Lin, Lizhu Hao
Summary: This paper introduces a self-organizing data-driven network with hierarchical pruning model using fuzzy neural network for fast-dynamics prediction in ship maneuvering. Through incremental training and hierarchical pruning mechanism, the model is able to accurately predict the velocity dynamics of the ship and achieve dynamic abstraction.
