Enhancing dissolved oxygen control using an on-line hybrid fuzzy-neural soft-sensing model-based control system in an anaerobic/anoxic/oxic process

2013 ◽  
Vol 40 (12) ◽  
pp. 1393-1401 ◽  
Author(s):  
Mingzhi Huang ◽  
Jinquan Wan ◽  
Kang Hu ◽  
Yongwen Ma ◽  
Yan Wang
Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1493
Author(s):  
Mantas Butkus ◽  
Donatas Levišauskas ◽  
Vytautas Galvanauskas

An adaptive control system for the set-point control and disturbance rejection of biotechnological-process parameters is presented. The gain scheduling of PID (PI) controller parameters is based on only controller input/output signals and does not require additional measurement of process variables for controller-parameter adaptation. Realization of the proposed system does not depend on the instrumentation-level of the bioreactor and is, therefore, attractive for practical application. A simple gain-scheduling algorithm is developed, using tendency models of the controlled process. Dissolved oxygen concentration was controlled using the developed control system. The biotechnological process was simulated in fed-batch operating mode, under extreme operating conditions (the oxygen uptake-rate’s rapidly and widely varying, feeding and aeration rate disturbances). In the simulation experiments, the gain-scheduled controller demonstrated robust behavior and outperformed the compared conventional PI controller with fixed parameters.


Author(s):  
V. Panov

This paper describes the development of a distributed network system for real-time model based control of industrial gas turbine engines. Distributed control systems contribute toward improvements in performance, testability, control system maintainability and overall life-cycle cost. The goal of this programme was to offer a modular platform for improved model based control system. Hence, another important aspect of this programme was real-time implementation of non-linear aero-thermal gas turbine models on a dedicated hardware platform. Two typical applications of real-time engine models, namely hardware-in-the-loop simulations and on-line co-simulations, have been considered in this programme. Hardware-in-the-loop platform has been proposed as a transitional architecture, which should lead towards a fully distributed on-line model based control system. Distributed control system architecture offers the possibility of integrating a real-time on-line engine model embedded within a dedicated hardware platform. Real-time executing models use engine operating conditions to generate expected values for measured and non-measured engine parameters. These virtual measurements can be used for the development of model based control methods, which can contribute towards improvements in engine stability, performance and life management. As an illustration of model based control concept, the example of gas turbine transient over-temperature protection is presented in this study.


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