Identification for control of suspended objects in non-Newtonian fluids

This paper proposes a framework for modelling velocity profiles and suspended objects in non-Newtonian fluid environment. A setup is proposed to allow mimicking blood properties and arterial to venous dynamic flow changes. Navier-Stokes relations are employed followed by fractional constitutive equations for velocity profiles and flow. The theoretical analysis is performed under assumptions of steady and pulsatile flow conditions, with incompressible properties. The fractional derivative model for velocity and friction drag effect upon a suspended object are determined. Experimental data from such an object is then recorded in real-time and identification of a fractional order model performed. The model is determined from step input changes during pulsatile flow for velocity in the direction of the flow. Further on, this model can be employed for controller design purposes for velocity and position in pulsatile non-Newtonian fluid flow

Mathematical modelling with experimental validation of viscoelastic properties in non-Newtonian fluids

The paper proposes a mathematical framework for the use of fractional-order impedance models to capture fluid mechanics properties in frequency-domain experimental datasets. An overview of non-Newtonian (NN) fluid classification is given as to motivate the use of fractional-order models as natural solutions to capture fluid dynamics. Four classes of fluids are tested: oil, sugar, detergent and liquid soap. Three nonlinear identification methods are used to fit the model: nonlinear least squares, genetic algorithms and particle swarm optimization. The model identification results obtained from experimental datasets suggest the proposed model is useful to characterize various degree of viscoelasticity in NN fluids. The advantage of the proposed model is that it is compact, while capturing the fluid properties and can be identified in real-time for further use in prediction or control applications. This article is part of the theme issue 'Advanced materials modelling via fractional calculus: challenges and perspectives'

Closed loop control of an electromagnetic stirrer in the continuous casting process

The continuous casting (CC) process is a crucial factor in determining quality of steel slabs, therefore directly affecting the scrap percentage and manufacturing costs. By braking or accelerating the liquid steel in the casting mould with the electromagnetic stirring (EMS) technique, the now speed can remain in an optimal range in terms of slab quality. The EMS device employed in the CC of ArcelorMittal (AM) Ghent is controlled with an inferential control strategy. Here, the state of the caster is mapped to an assumed flow speed (which is not measured), revealing the need to brake or accelerate. By measuring the flow speed, using a sensor for the drag force, it was revealed that the flow is often too fast and drifts out of the optimal range, even if the machine state does not change. This paper presents the study performed to improve the current operation. A static model relating the electric current in the EMS device to the steel flow speed was derived, as well as a dynamic model. From the static model, a new inferential control strategy was proposed. Additionally, several dynamic closed loop controllers have been tested in simulations. Our study indicates that real plant implementation is feasible

Control of Continuous Casting Process Based on Two-Dimensional Flow Field Measurements

Two-dimensional flow field measurement allows us to obtain detailed information about the processes inside the continuous casting mould. This is very important because the flow phenomena in the mould are complex, and they significantly affect the steel quality. For this reason, control based on two-dimensional flow monitoring has a great potential to achieve substantial improvement over the conventional continuous casting control. Two-dimensional flow field measurement provides large amounts of measurement data distributed within the whole cross-section of the mould. An experimental setup of the continuous casting process called Mini-LIMMCAST located in Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany, is used for this thesis. This thesis examines two alternatives of flow measurement sensors: Ultrasound Doppler Velocimetry (UDV) and Contactless Inductive Flow Tomography (CIFT). Both sensor variants can obtain information on the velocity profile in the mould. Two approaches were considered to create the process model needed for model-based control: a spatially discretized version of a model based on partial differential equations and computational fluid dynamics and a model obtained using system identification methods. In the end, system identification proved to be more fruitful for the aim of creating the model-based controller. Specific features of the flow were parametrized to obtain the needed controlled variables and outputs of identified models. These features are mainly related to the exiting jet angle and the meniscus velocity. The manipulated variables considered are electromagnetic brake current and stopper rod position. Model predictive control in several versions was used as the main control approach, and the results of simulation experiments demonstrate that the model predictive controller can control the flow and achieve the optimum flow structures in the mould using UDV. CIFT measurements can provide similar velocity profiles. However, further technical developments in the CIFT sensor signal processing, such as compensating for the effects of the strong and time-varying magnetic field of the electromagnetic brake on CIFT measurements, are necessary if this sensor is to be used for closed-loop control.Two-dimensional flow field measurement allows us to obtain detailed information about the processes inside the continuous casting mould. This is very important because the flow phenomena in the mould are complex, and they significantly affect the steel quality. For this reason, control based on two-dimensional flow monitoring has a great potential to achieve substantial improvement over the conventional continuous casting control. Two-dimensional flow field measurement provides large amounts of measurement data distributed within the whole cross-section of the mould. An experimental setup of the continuous casting process called Mini-LIMMCAST located in Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany, is used for this thesis. This thesis examines two alternatives of flow measurement sensors: Ultrasound Doppler Velocimetry (UDV) and Contactless Inductive Flow Tomography (CIFT). Both sensor variants can obtain information on the velocity profile in the mould. Two approaches were considered to create the process model needed for model-based control: a spatially discretized version of a model based on partial differential equations and computational fluid dynamics and a model obtained using system identification methods. In the end, system identification proved to be more fruitful for the aim of creating the model-based controller. Specific features of the flow were parametrized to obtain the needed controlled variables and outputs of identified models. These features are mainly related to the exiting jet angle and the meniscus velocity. The manipulated variables considered are electromagnetic brake current and stopper rod position. Model predictive control in several versions was used as the main control approach, and the results of simulation experiments demonstrate that the model predictive controller can control the flow and achieve the optimum flow structures in the mould using UDV. CIFT measurements can provide similar velocity profiles. However, further technical developments in the CIFT sensor signal processing, such as compensating for the effects of the strong and time-varying magnetic field of the electromagnetic brake on CIFT measurements, are necessary if this sensor is to be used for closed-loop control.