A Model-Based Improved Control of Dissolved Oxygen Concentration in Sequencing Wastewater Batch Reactor

The paper presents aspects related to the design and implementation of a cascade control solution (CCS), which is tested on laboratory equipment meant for the position control of a ferromagnetic sphere in a Magnetic Levitation System with Two Electromagnets (MLS2EM). The nonlinear mathematical model (MM) of the MLS2EM is derived on the basis of the first principles equations with experimentally identified parameters. This MM is next linearized at two operating points. The CCS includes a state feedback controller in the inner loop and a model predictive controller in the outer loop. Experimental results are given in order to validate the proposed CCS and to illustrate the performance of the position control system expressed as very good dynamics and zero steady-state control error.

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“…These solutions will be supported by fuzzy logic and other strategies [23]- [29] in order to cope with several nonlinear processes.…”

Section: Discussionmentioning

confidence: 99%

Model predictive control solution for magnetic levitation systems

Bojan-Dragoş

Stînean

Precup

et al. 2015

2015 20th International Conference on Methods and Models in Automation and Robotics (MMAR)

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“…Major changes affect the values of learning rates, anti-windup filter parameters and DMRAC starting points, which can be now adjusted during the optimization process to meet various conditions. In addition, the anti-windup filter reduces the impact of the control signal constraints, such as maximum rotational speed of blowers [27][28][29]. This part of the control system uses the control error e DO and Q air to calculate the Q air ref for the lower-level controller mentioned above.…”

Section: General Work Cycle Of the Implemented Systemmentioning

confidence: 99%

Improving SBR Performance Alongside with Cost Reduction through Optimizing Biological Processes and Dissolved Oxygen Concentration Trajectory

2019

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Authors of this paper take under investigation the optimization of biological processes during the wastewater treatment in sequencing batch reactor (SBR) plant. A designed optimizing supervisory controller generates the dissolved oxygen (DO) trajectory for the lower level parts of the hierarchical control system. Proper adjustment of this element has an essential impact on the efficiency of the wastewater treatment process as well as on the costs generated by the plant, especially by the aeration system. The main goal of the presented solution is to reduce the plant energy consumption and to maintain the quality of effluent in compliance with the water-law permit. Since the optimization is nonlinear and includes variations of different types of variables, to solve the given problem the authors performed simulation tests and decided to implement a hybrid of two different optimization algorithms: artificial bee colony (ABC) and direct search algorithm (DSA). Simulation tests for the wastewater treatment plant case study are presented.

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“…This approach was applied for modelling different plants, e.g. Kartuzy aeration system [19][20][21], Nowy Dwor Gdanski aeration system [22] and Swarzewo aeration system [18,23]. The model of the Swarzewo aeration system was first presented in [18].…”

Section: Mathematical Model Of the Aeration Systemmentioning

confidence: 99%

Nonlinear Fuzzy Control System for Dissolved Oxygen With Aeration System in Sequencing Batch Reactor

Piotrowski

Skiba

2015

ITC

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Biological processes at a wastewater treatment plant are complex, multivariable, time varying and nonlinear. Moreover, interactions between the components are very strong. Control of dissolved oxygen is one of most important task at the plant. The level of dissolved oxygen in aerobic tanks has significant influence on behaviour and activity of microorganisms at the plant. Air for aerated tanks is supplied by the aeration system (blowers, pipes, diffusers), which is a complicated nonlinear dynamical system. A fuzzy control system for tracking the dissolved oxygen reference trajectory in activated sludge processes was proposed and investigated. The sequencing batch reactor was considered. The nonlinear aeration system dynamic was included. Two systems (sequencing batch reactor, aeration system) were modelled and validated. Inverse model of an aeration system was used to control system design. Dissolved oxygen is the control input, while the rotational speed and blowers on/off are control outputs. The nonlinear fuzzy control system was tested by simulation based on real data records sourced from a case study plant located in Swarzewo, Northern Poland.

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A Model-Based Improved Control of Dissolved Oxygen Concentration in Sequencing Wastewater Batch Reactor

Cited by 20 publications

References 14 publications

Model predictive control solution for magnetic levitation systems

Model predictive control solution for magnetic levitation systems

Improving SBR Performance Alongside with Cost Reduction through Optimizing Biological Processes and Dissolved Oxygen Concentration Trajectory

Nonlinear Fuzzy Control System for Dissolved Oxygen With Aeration System in Sequencing Batch Reactor

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