In this work, we design an output predictive controller that operates a common class of activated sludge plants. The controller solves a state-feedback model predictive control problem in which the process state and d...
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In this work, we design an output predictive controller that operates a common class of activated sludge plants. The controller solves a state-feedback model predictive control problem in which the process state and disturbances are determined by a moving horizon estimator. We illustrate the behaviour of the controller when operating the plant to produce an effluent water of varying nitrogen content. The close tracking of the effluent profiles is enforced by stabilizing the system around optimal steady-state points that satisfy the output reference trajectories. Considering the generality of the formulation, the predictive controller can be configured to operate this class of activated sludge plants to achieve alternative objectives.
We report the preliminary results of a feasibility study in which we investigate the possibility to operate a common class of activated sludge plants to produce effluent wastewater of varying quality for crop irrigati...
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We report the preliminary results of a feasibility study in which we investigate the possibility to operate a common class of activated sludge plants to produce effluent wastewater of varying quality for crop irrigation. Firstly, a nitrogen reference trajectory is computed as solution to a higher-level optimal control problem that aims at maximizing plant biomass in a crop growth system. We then study how to control the treatment plant with a zero-offset predictive control strategy designed to operate the treatment process to supply nitrogen according to this optimal planning for crop growth. We show how an ad hoc tuning of the predictive controller allows to define alternative policies that favour the manipulation of different forms of nitrogen in the treatment plant. We show that the designed controllers are only partially capable to operate the treatment plant to meet the nitrogen demand, when subjected to typical municipal wastewater influent conditions. However, zero-offset can be achieved under constant influent conditions. We analyse the performance of the controller in terms of tracking accuracy and operational energy.
In this work, the full-state observability properties of a class of biological wastewater treatment plants are analysed. Specifically, the five biological reactors and the secondary settler in the Benchmark Simulation...
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In this work, the full-state observability properties of a class of biological wastewater treatment plants are analysed. Specifically, the five biological reactors and the secondary settler in the Benchmark Simulation Model no. 1 are studied. For the task, we represented the activated sludge plant as a dynamical system consisting of 145 states, 8 controls, 14 disturbances and 12 outputs and as a complex network to study its observability properties from a structural and a classical point of view. By analysing the topology of the network, we show how the system is not observable in the structural sense and thus how it is also not observable in the classical sense for all possible realisations of its parameters. As this is also true for a linearisation commonly used in the literature, we analysed a reduced-order system that, based on such linearisation, does not consider the state variables corresponding to dissolved oxygen and alkalinity in the upper-layers of the settler. We show how this system configuration is only observable in a structural sense.
In this work, the full-state controllability properties of a biological wastewater treatment plant are analysed. Specifically, the five biological reactors in the Benchmark Simulation Model no. 1 are studied. For the ...
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ISBN:
(数字)9783907144022
ISBN:
(纸本)9781728188133
In this work, the full-state controllability properties of a biological wastewater treatment plant are analysed. Specifically, the five biological reactors in the Benchmark Simulation Model no. 1 are studied. For the task, we represented the activated sludge plant as a dynamical system consisting of 65 states, 7 controls and 27 disturbances as a complex network and we studied its controllability properties from a classical and a structural point of view. By analysing the topology of the network, we show how the system is controllable in the structural sense and thus how it is controllable in the classical sense for almost all realisations of its parameters. Interestingly, we also found that the linearisation around a fixed point commonly used in the literature leads to a realisation of the system that is not full-state controllable in the classical sense. We show how this realisation is controllable if the state variables associated with inert matter are not considered. We quantify the compound and individual control efforts of this reduced-order system in terms of energy-based controllability metrics.
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