caa a22 4500 606160078 CHVBK 20210128100628.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00521-015-1858-3 doi (NATIONALLICENCE)springer-10.1007/s00521-015-1858-3 An adaptive control method for the dissolved oxygen concentration in wastewater treatment plants [Elektronische Daten] [Mei-Jin Lin, Fei Luo] The activated sludge process plays a vital role in the treatment of the civil wastewater. In the operation of the activated sludge process, a key variable is dissolved oxygen (DO) concentration. In this paper, a neural nonlinear adaptive control design technique is presented to solve the DO concentration control problem for an uncertain wastewater treatment process. In the controller design, all uncertain dynamics of the wastewater treatment are approximated by using radial basis function neural networks. Then, it is rigorously proved that semiglobal uniform ultimate boundedness of all the closed-loop system signals is guaranteed by the Lyapunov method. Finally, simulation studies are performed to demonstrate the effectiveness of the proposed adaptive controller. Comparing with the existing controllers, simulation results show that a satisfactory performance is obtained using the proposed adaptive controllers. The Natural Computing Applications Forum, 2015 Adaptive control nationallicence Neural networks (NNs) nationallicence Dissolved oxygen concentration nationallicence Activated sludge process nationallicence Lin Mei-Jin College of Automation Science and Engineering, South China University of Technology, 510641, Guangzhou, China aut Luo Fei College of Automation Science and Engineering, South China University of Technology, 510641, Guangzhou, China aut Neural Computing and Applications Springer London 26/8(2015-11-01), 2027-2037 0941-0643 26:8<2027 2015 26 521 https://doi.org/10.1007/s00521-015-1858-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-015-1858-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Lin Mei-Jin College of Automation Science and Engineering, South China University of Technology, 510641, Guangzhou, China aut NATIONALLICENCE 700 1- Luo Fei College of Automation Science and Engineering, South China University of Technology, 510641, Guangzhou, China aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/8(2015-11-01), 2027-2037 0941-0643 26:8<2027 2015 26 521