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The impact of multi-layered electrode microstructures on the dynamic capacitance of electrochemical double layer supercapacitors is investigated. An electrochemical model that describes ion diffusion and double layer dynamics across the layered electrodes is first developed and then matched to experimental data. With TiO2 particulate and carbon nanotube layered electrodes, two knee frequencies were observed in the real and imaginary capacitance plots in both experiment and model simulations. These two knee frequencies resulted in an increase in real capacitance at high frequencies (ω ≈ 100 − 102 rad s−1) but a reduction at lower frequencies (ω ≈ 10−2 rad s−1), with the response being largely insensitive to the relative layer thicknesses. The increased capacity at high frequencies was due to increased ion mobility across the electrodes caused by the layering, allowing diffusion limitations of identical homogeneous electrodes to be overcome. These results imply the suitability of layered electrodes for applications with highly dynamic charge profiles and/or relatively thick electrodes.

Radial-axial ring rolling (RARR) is an industrial forging process that produces seamless metal rings with uniform cross-section using one radial and one axial rolling stage. Conventionally, the ring products are circular and the process is tightly constrained using guide rolls for stability, and to ensure the circularity and uniformity of the ring. Recent work has shown that when guide rolls are omitted, stability can be maintained using differential speed control of the roll pairs. However, achieving uniform curvature in this unconstrained configuration was not always possible when the controller only centred the ring within the rolling mill. In addition to the regulation of constant curvature in circular rings, differential speed control in unconstrained rolling offers an opportunity to bend the ring about the mandrel to create shapes with nonuniform curvature, for example: squares, hexagons, rings with flat sections, etc. We describe a control technique for creating non-circular rings using the rolling hardware of a conventional RARR mill, machine-vision sensing and differential speed control of the rolling stages. The technique has been validated for an industrial material in numerical simulations using the finite element method and also demonstrated on a desktop-scale RARR mill using modelling clay to simulate metal at elevated process temperatures.

Synchrotrons are used to generate light for academic and industry research by accelerating electrons travelling in a circular path to relativistic speeds. In order to achieve optimum performance, electron beam stability is a crucial parameter for synchrotrons. This paper describes the design of a beam stabilisation controller, using Internal Model Control. Basis functions are used to identify the controllable components of the system and it is demonstrated how by selecting dynamics for each spatial mode, enhanced performance is achieved. The robust stability of the controller in the presence of spatial uncertainties is developed within an Integral Quadratic Constraint framework using two methods of spatial decomposition: Singular Value decomposition and Fourier decomposition. The controller has been implemented at Diamond Light Source, the UK׳s national synchrotron science facility. Results from the controller implementation are presented and it is demonstrated how the controller design and robust stability analysis are used to tradeoff performance and robustness.

Parameter estimation of a supercapacitor model that uses PDEs to describe electrochemical physical phenomena is studied. The model parameters were identified from time domain charge/discharge data and also from frequency domain data in the form of electrical impedance spectroscopy at different open cell voltages. The identified physical model could fairly accurately simulate the experimental data, however, this accuracy was found to drop off at high frequencies. The performance of the physical model was compared to a second order circuit, with the two models having similar levels of accuracy. The circuit was found to be simpler to implement but, unlike the physical model, could not supply physical information about the internal state of the supercapacitor.

Demand side management (DSM) is a key concept for smart grid. In order to achieve DSM, network stress information needs to be provided to the users, which normally requires two-way communication between users and an upper level control centre. Implementing such communication in large scale power networks will be both costly and introduces problems with security and privacy of data. On-load tap changes (OLTC) are used to adjust the voltage at the users' side in response to network conditions. By detecting tap changes, an indication of the level of network stress can be provided to users without communicating with a control centre, which provides an economical and efficient measure for network stress. This paper presents a tap change detection algorithm based on Hilbert-transform phase-locked loops, Q-R decomposition windowed recursive least square algorithm and a hypothesis test, which can distinguish tap changes made by an OLTC transformer from the fluctuation in voltage caused by changes in loads. In this paper, the tap change detection algorithm is illustrated and the results for both simulated input and real-time data are presented and discussed.

An increasing awareness of energy efficiency has led to the development of several improved converter topologies, semiconductor devices and control schemes for distributed energy resources, and, particularly, for microgrids. Recent advances in energy management systems (EMS) for microgrids have improved upon existing methods in several aspects, including prediction of power generated by photovoltaics (PV), and optimal management of electrical energy storage. However, the actual generated PV power may deviate from predictions for several reasons, such as rapid cloud changes or system faults. This paper contributes to the ongoing research on EMS control schemes by proposing a model predictive control (MPC) scheme that adapts to the difference between the actual and predicted output power of PV. The key benefit of this approach is its ability to rapidly adapt to varying operating conditions of the PV without increasing the computational burden of a typical MPC scheme. The feasibility of the scheme is demonstrated using simulations of 5 kW microgrid system compromising a 5 kW/400 Ah battery, 10 kW PV and 5 kW grid/load connection. The proposed scheme reduces variations in the state of charge (SOC) of a battery. The proposed scheme also reduces the energy taken from grid and this improvement in performance is a function of the difference between the actual and the predicted power.

Reducing greenhouse gas emissions is now an urgent priority. Systems control theory, and in particular feedback control, can be helpful in designing policies that achieve sustainable levels of emissions of CO 2 (and other greenhouse gases) while minimizing the impact on the economy, and at the same time explicitly addressing the high levels of uncertainty associated with predictions of future emissions. In this paper, we describe preliminary results for an approach where model predictive control (MPC) is applied to a model of the UK economy (UK 4see model) as a test bed to design sustainable policies for greenhouse gas emissions. Using feedback control, the policies are updated on the basis of the actual emissions, rather than on the predicted level of emissions. The basic structure and principle of the UK 4see model is described and its implementation in Simulink is presented. A linearized state space model is obtained and model predictive control is applied to design policies for CO 2 emissions. Simulation results are presented to demonstrate the effectiveness of the proposed method. The preliminary results obtained in this paper illustrate the strength of the proposed design approach and form the basis for future research on using systems control theory to design optimal sustainable policies. © 2012 Elsevier Ltd. All rights reserved.

By accelerating electrons to relativistic speeds, synchrotrons generate extremely intense and narrow beams of electromagnetic light that are used for academic research and commercial development across a range of scientific disciplines. In order to achieve optimum performance, the stability of the electron beam is a crucial parameter for synchrotrons and is achieved by a beam stabilisation system that is used to control the location of the electron beam and minimise any instability of the electron beam caused by external disturbances. Slew rate limits are common nonlinearities encountered with the actuators in synchrotron feedback systems which can impose significant limitations on the robustness and the performance of the control system. This paper describes an Internal Model Control (IMC) based anti-windup synthesis using an algebraic Riccati equation for a discrete-time control system to compensate against the performance deterioration in the presence of rate constraints. An Integral Quadratic Constraint (IQC) framework is used to analyse the robust stability of the anti-windup augmented closed loop system in the presence of norm-bounded uncertainty. The anti-windup augmented controller is implemented at Diamond Light Source, the UK’s national synchrotron facility and improvements in robustness and performance were achieved with respect to the use of no anti-windup compensation.

Ring-rolling is an industrial forming process for producing high-strength seamless metal rings up to 6m diameter. Thick-walled cylindrical rings of material, typically metallic alloys, are compressed between two or more internal and external rollers and rotated until a target geometry, often outer diameter, is achieved. A common plant configuration is that of a pair of radially acting rollers and a pair of axial rollers, the radial-axial ring rolling (RARR) machine. The most commonly produced product geometries have an axisymmetric cross-section profile. However, during the forming process the cross section is changed significantly as it passes through each pair of rollers. This irregular shape hinders geometry state measurement and this complicates modelling and control of the process. Recent developments in sensing capabilities offer high resolution measurement of ring geometry during forming. In this work, we present advances in these sensing techniques, a numerical method for storing and predicting the ring's geometrical state and control laws to achieve a non-axisymmetric cross-section profile in rolled rings using existing RARR plant hardware.

Actuators that bend slice lips are commonly used in cross-directional (CD) control systems for paper making and plastic film extrusion. A dynamic model of these actuators is developed, which is used to investigate their spatial modes and dynamic responses. The model shows that both the shape and the amplitude of the spatial response depend upon the stiffness of the slice lip. The design of most practical CD control systems is simplified by assuming that the spatial and dynamic responses are separable in the sense that each of the spatial modes has the same dynamics. The validity of this assumption is examined and it is shown that subject to conditions that are likely to be satisfied in practice, the responses can be taken as separable. The model is verified using data from plastic film extrusion line and the consequences of separability for the design of CD control systems are discussed.

In this study, operating conditions for a batch fluidised bed dryer are found that achieve the specifications on the final moisture level, while minimising the energy consumption. The operating conditions are obtained by solving an optimisation problem, where the specification for the final moisture content of the bed is included as a constraint. The optimisation is based on a lumped mechanistic model that describes the heat and mass transfer between solid, gas and bubble phases in the bed. Experimental validation of this model shows that it can be used to predict the particle moisture content and temperature profiles during the drying process and it is shown that the wall temperature has a major effect on the predictions. Compared to the standard approach of maintaining the inlet air temperature and flow rate at constant values, the optimal operating conditions for a lab-scale bed dryer reduce the energy consumption by 26% and shorten the duration of a batch by 20 min.

A computationally efficient reduced model estimator is described for determining the effective position of actuators used for cross-directional control in web processes. The estimator is represented as a Radial Basis Function Network, where the basis functions in the hidden layer are defined using discrete Chebyshev polynomials. The problem is considered as a nonlinear optimization problem and solved online using a recursive prediction error method. Convergence analysis is used to compare the performance of both full and reduced model estimators, with the advantages of the reduced model being demonstrated using results obtained from an industrial plastic film extrusion test bed.

Industrial web processes are usually treated by control engineers as special forms of multivariable system. However, based upon fundamental modelling arguments, more natural paradigms emerge two dimensional (2D) dynamical systems and orthogonal transform processes. This approach is followed here, along with the associated estimation and control algorithms. The important issue of dimensionality is also addressed and control specific data compression methods are discussed as are the data collection and sensing issues which are specific to web forming processes. All the methods discussed use synthesis procedures and thus have a natural adaptive interpretation.

Ring-rolling is an industrial forming process to produce high-strength metal rings up to 6m diameter. Thick-walled cylindrical workpieces of material, typically metallic alloys, are compressed between two or more internal and external rollers and rotated until a target geometry, often outer diameter, is achieved. The process is inherently unstable and the process is often constrained and/or controlled to improve its stability. This paper presents an image processing algorithm for the measurement of ring geometry through photogrammetry in real-time. These measurements will form part of the feedback control system for a ring-rolling process. An off-the-shelf USB webcam is used to capture images of the ring during forming and the scene is controlled to maximise contrast and minimise occlusions of the ring. The image processing tasks include object identification, edge detection, outlier rejection and distortion rectification. The process has been implemented on a desktop-scale forming machine and has been shown to work at rates suitable for control the ring-rolling process using feedback.

Commercial pressures on metal strip manufacturers drive ever greater demands on the control of residual stress distributions within the finished strip. Rolling mills in current use have a range of actuators available to attempt this control and new designs are being offered with arrays of similar actuators distributed across the width of the mill. The interaction of these actuators motivates a thorough analysis of spatial control in strip metal rolling. This paper takes theory that has been successfully applied to the paper and plastics industry and applies it for the first time to the strip rolling process, giving a toolkit for the analysis and design of current and future cross-directional control systems. Data from a state of the art commercial mill is used to allow characterization of typical error signals in terms of orthogonal basis functions. Actuators are analyzed to show how much power they have within the "spectrum" of this basis function expansion. Sensors are analyzed to show their filtering effect within the spectrum. The consequent theory is used to give a rationale to future actuator design and a benchmark for the assessment of control performance with existing actuators. Two control strategies are investigated and compared-minimum variance and mini-max-and their achievements characterized. Control system sensitivity is assessed.

This paper considers suitable disturbance models for use in the design of control systems for web forming processes. It suggests a practical disturbance representation and, using spectral factorization, presents a multivariable aggregated model of the disturbance. The paper compares generalized minimum variance (GMV) controllers designed using uncorrelated and correlated disturbance models and demonstrates the improvement in performance of a multivariable GMV controller which is designed to accommodate the cross direction correlation in the disturbance compared to the GMV controller that is commonly used in practice, which is based on a model that ignores the effects of correlated disturbances.

Reducing greenhouse gas emissions is now an important and urgent matter. A key observation is that systems control theory can be used to design the optimal policy that both achieves sustainable levels of emissions of CO2 (and other greenhouse gases) and minimises the impact on the economy, while explicitly addressing the high levels of uncertainty associated with predictions of future emissions. As an initial result, in this paper a test bed for the above approach the UK 4see model is introduced, which is suitable for using control theory to design sustainable policies for greenhouse gas emissions. The basic structure and principle of the model is described and its implementation in Matlab Simulink is presented. A linearised state space model is then obtained, analysed and further simplified via standard model reduction techniques. The model established in this paper provides a method of predicting future greenhouse gas emission levels and economic growth against different energy policies and forms the basis for future research on using systems control theory to design optimal sustainable policies. © 2011 IEEE.

Network Rail's Western Route is undergoing a wide-ranging modernisation programme, with £7.5bn investment in 175 miles of electrification and infrastructure upgrades allowing the introduction of four new fleets of train by 2019. This paper reviews the potential utilisation of camera imagery to inform maintenance processes that need to absorb a step change in pantograph movements and OLE management.

Cross-directional (CD) control systems regulate product properties in industrial web processes by manipulating the inputs to arrays of actuators. In many of these processes, the product wanders or undergoes transformations such as stretching that introduce lateral shifts in the location of the actuator responses. The spatial position of the center of the response of each actuator is known as the actuator mapping and for CD controllers to operate effectively, it is important that this is known accurately. Actuator mapping is one of the main sources of uncertainty in the model that is used to design CD controllers and mismapping can lead to closed-loop instability, so CD controllers are often designed conservatively to provide robustness to this uncertainty. Because CD controllers can operate with a significant level of mismapping, both the dynamic and steady-state responses of the closed-loop system are often degraded. In practice, it is difficult to detect the presence of mismapping, but this brief describes an online diagnostic technique based on a vector auto regression (VAR) representation of the closed-loop response of the actuator inputs, which derives a statistic from existing plant data that can be used in a hypothesis test to detect the presence of mismapping. The performance of the technique is demonstrated by results from an implementation on a plastic film process. © 2009 IEEE.

In this paper, a distributed parameter approach is used to model and control a batch fluidised bed dryer. Electric capacitance tomography (ECT) is used as a sensor to measure and control the distributed permittivity in the bed. First, a lumped model is developed to describe the heat and mass transfer between solid, gas and bubble phases in the bed. Then, based on this model, a distributed parameter model is developed to predict the permittivity distribution. Experimental validation confirms the accuracy of the model. Finally, a distributed parameter controller is designed and implemented to regulate the permittivity distribution.

The accuracy of flexible forming processes with mobile tools is generally insufficient for industrial needs. Modern stereovision cameras should allow geometric feedback to improve accuracy, but to date it has been assumed that on-line control is in practice impossible because non-linear process models are too slow. This paper demonstrates for the first time that an appropriate process model can be formed from a set of spatial impulse responses found by linearisation around a pre-planned tool path. This allows on-line feedback control of part geometry. A general formulation is presented, and is evaluated through application to an axisymmetric incremental sheet forming process.

In this paper, the implementation of an observer with an electrochemical supercapacitor model is discussed. Using Lie derivatives, the model was shown to be locally nonlinear observable. When the two transference numbers, related to ion mobility, were selected to be equal, the model became linear and the states relating to ionic concentration became unobservable. These unobservable states were shown to not satisfy the weaker detectability condition. The energy storage characteristic of supercapacitors meant that they incorporated integrator dynamics and this led to random walk trajectories with a Kalman filter implementation. This problem could be corrected by using a more suitable observer or by introducing a control system such that the model becomes asymptotically stable. The comments on observer performance made in this paper could be applied to more complex electrochemical models, such as those for Lithium ion batteries, as they use many similar physical relationships.

This paper presents the design and implementation of prototype periodic l∞ control systems for governing the temperature profile of a spray-form tooling process that is used in rapid manufacture of tooling. The controllers are based on discrete time varying l∞ theory for periodic/almost periodic linear systems. After a brief description of the process in study and its mathematical modelling, the paper formulates the control problem and investigates its design and characteristic features. The theoretical issues are accompanied with simulation and experimental studies on a real spray-form apparatus. The paper shows that the performance of the proposed controllers is better than previous control designs. This is the first ever application of l∞ control systems for spray-form tooling processes, something that reflect their characterization as prototypes. © 2006 Elsevier Ltd. All rights reserved.

Many modern spray deposition processes, such as spray painting or coating, are automated by using a robot to move an applicator in a series of passes over the surface being sprayed. Determining the robot path that creates the required coat thickness over the surface can be considered as an optimization problem, which traditionally has been solved in the spatial domain. In this paper, results from sampling theory are used to transfer the problem into the spatial frequency domain, which determines the optimal separation between passes. The paper also shows how angled raster patterns can be combined to provide a continuous path over the surface that generates the required distribution of deposited material. Note to Practitioners-This paper is motivated by the problem of producing a given distribution of coat thickness during an automated spraying or deposition process. The coating is applied by an applicator that is moved by a robot whose path consists of a series of passes over a surface, and the aim is to determine the separation between the passes and the changes to the deposition rate or robot velocity that will produce the required thickness distribution. In many applications, a uniform thickness is required over the surface, but this paper also considers the problem of producing a shaped thickness profile. The analysis uses ideas from Shannon's sampling theorem to move the problem into the frequency domain, which provides a direct link between the Fourier transform of spray footprint on the surface and the separation of passes of the applicator as it moves over the surface. The paper also introduces a scanning strategy that consists of a combination of two sets of angled raster scans. Compared to paths consisting of conventional scans, this has the advantage that it reduces the time that the robot spends off the edge of the surface.

Electromagnetic energy in the microwave and radio-frequency (RF) portions of the spectrum can be used to heat or defrost (thaw) foodstuffs. This paper considers a fixed frequency RF oven, where a matching circuit is used to ensure that the combined impedance of the oven and the food (the load) matches the impedance of the generator and the transmission line. A controller measures the reflected RF signal and adjusts the settings of components in the matching circuit. The system is highly nonlinear and there are significant sources of uncertainty in the model of the process. A variable structure controller is designed and its stability is examined in the presence of uncertainties due to stray components. The switching lines are defined in terms of the real and imaginary parts of the reflected signal, which avoids the need to estimate the states. Conditions are derived for maintaining stability in the region close to the matching point. The performance of the controller is illustrated by results from an implementation on a prototype commercial RF oven.

Process tomography is a sensing technique that can be used to measure distributed flows inside pipes. As a result, it is suitable for use as the sensor in a feedback control system for regulating the concentration of a substance in a fluid flow along the pipe. This paper describes such a control system and starts by developing a model based on the convection-diffusion equation, which describes the diffusion of a substance within the fluid flow, and then develops a state space description of the system. The state space model is used as the basis of a state feedback design. Estimates of the states are obtained from an observer that uses the measurements obtained by the tomographic sensor. A simulation of a feedback system based upon proportional plus integral control is presented.

Annual deaths from scarlet fever in Liverpool, UK during 1848–1900 have been used as a model system for studying the historical dynamics of the epidemics. Mathematical models are developed which include the growth of the population and the death rate from scarlet fever. Time-series analysis of the results shows that there were two distinct phases to the disease (i) 1848–1880: regular epidemics (wavelength = 3.7 years) consistent with the system being driven by an oscillation in the transmission coefficient (δβ) at its resonant frequency, probably associated with dry conditions in winter (ii) 1880–1900: an undriven SEIR system with a falling endemic level and decaying epidemics. This period was associated with improved nutritive levels. There is also evidence from time-series analysis that raised wheat prices in pregnancy caused increased susceptibility in the subsequent children. The pattern of epidemics and the demographic characteristics of the population can be replicated in the modelling which provides insights into the detailed epidemiology of scarlet fever in this community in the 19th century.

The control strategy is based on minimising the expected range of variations observed within a single scan across the width of the sheet. This can be considered as an l∞ minimisation problem and implemented using efficient algorithms based on the simplex method of linear programming. The BIBO stability of the controlled system is analysed and it is shown that the stability of the full multivariable system is determined by the stability of a scalar dynamic term. In general, the controller is suboptimal in the sense that it minimises an upper bound on the expected range of variations across the sheet, but for a certain class of disturbance models the expected value of the range can be minimised optimally by using the minimum variance solution.

This paper addresses the problem of estimating the effective actuator centre locations in a paper machine whilst the process is operating in closed loop. A reduced order estimator employing a Radial Basis Function Network is described, where the basis functions in the hidden layer are defined using Discrete Chebyshev Polynomials. The problem is considered as a nonlinear optimisation problem and solved online using a recursive prediction error method.

Cross-directional control systems have been installed on a wide range of web processes, and many of these systems use an array of actuators to control cross-directional variations. This paper investigates the controllable bandwidth of these systems by using the concept of spatial frequencies to separate the controllable and uncontrollable components of a cross-directional disturbance. This leads to an expression for the spatial bandwidths of the whole array in terms of the spatial-frequency response of a single actuator. The analysis is closely related to Shannon's sampling theory, and a phenomenon similar to aliasing occurs when the spacing between the actuators is too large. A practical specification for the design of an array of actuators is given in terms of the spatial bandwidth of an individual actuator.

Synchrotron light sources can produce very intense beams of X-rays and ultra violet light for a range of applications, including protein crystallography, materials characterization and high resolution imaging. The Diamond Light Source is a 3rd generation synchrotron that has recently been constructed near Oxford, United Kingdom, which produces a 3 GeV electron beam in a ring of circumference of over 560 m. A key requirement of the process is that the vertical and horizontal location of the beam should be controlled to within 10% of the beam size, which corresponds to the RMS variation being less than 12.3 μm in the horizontal direction and 0.6 μm in the vertical direction. The beam location is subjected to disturbances caused by the effects of Insertion Devices and the effect of ground motion, particularly between 16 Hz and 30 Hz, where the ground motion is amplified by the resonances of the girders supporting the ring magnets. To achieve the specification, a fast beam stabilization feedback system is used to regulate the horizontal and vertical position of the beam in the presence of disturbances in the range 1 Hz to 100 Hz, using 170 sensors and actuators in both planes, positioned around the ring at a sampling rate of 10 kHz. This paper describes the design of the controller for this system and the results from the implementation are shown.

Model Predictive Control (MPC) has been applied in a range of industrial applications, and part of its popularity is that it can cope with a constrained system, providing an optimal control for a certain performance index. Incremental Sheet Forming (ISF) is an emerging progressive sheet metal forming technology where the deformation occurs locally. It is best suited to customised and one-off or short-run production, because ISF does not require costly individual tools, dies or punches to be manufactured. The geometrical accuracy of the shape made by ISF, is however, lower than the conventional processes, such as stamping. We address this issue by using a constrained model predictive control scheme to optimise the tool trajectory of this process. A simplified linear forming process model is first derived, which is modified then to handle the “tool contact” issue and after that a full MPC formulation is established. Two types of shapes are produced on an experimental rig, and the experimental results show that the final geometrical errors can be reduced compared to a standard contour following approach.

The shaping and forming of metal sheet is a key manufacturing process. Incremental Sheet Forming (ISF) is a novel sheet metal forming technology where the deformation of the metal sheet occurs locally and progressively. Currently, the geometrical accuracy of the shape made by ISF is low compared to shapes made by a stamping process. We address this issue by adopting a linear forming process model based on spatial impulse responses and applying a predictive control scheme to generate an optimised toolpath. Two optimisation strategies are compared based on non-negative least square(NNLSQ) and robust least square(RLSQ) algorithms, and the results suggest the NNLSQ is a better choice in terms of the final geometrical accuracy using a MPC regime.

Mathematical modeling, computational fluid dynamics (CFD) analysis and electrical capacitance tomography (ECT) is used to develop an understanding of batch fluidized-bed drying, which is a complex air-solids, multiphase process. The mathematical model is based on a three-phase theory that describes the mass-and heat-transfer between the air and solids phases. The CFD model is based on a two-fluid model (TFM) approach, in which both phases are considered to be continuous and fully interpenetrating. The hydrodynamic parameters used to model the heat-and mass-transfer between the two phases are determined by a correlation approach, and the estimated parameters are incorporated into a user defined function (UDF) in FLUENT. The moisture diffusion in the air and solids phases is simulated using the user defined scalar (UDS) transport equation in the software package. ECT is used for the online solids concentration and moisture measurement, based on dynamic calibration. Comprehensive comparisons between results from mathematical modeling, CFD simulation and ECT measurement are presented, and are validated using experiment results. Online measurement of moisture content is compared with a static calibration. The mathematical model, CFD and ECT presented are being integrated into an online process control system for a batch fluidized-bed drying application in the pharmaceutical industry. © 2007 American Institute of Chemical Engineers AIChE J, 2008

Control of a batch fluidized bed dryer is required in many industries. In this paper, the optimization and feedback control of material moisture content in a batch fluidized bed dryer are studied. The optimal operating conditions of the dryer have been found and a generic model control (GMC) strategy has been implemented to achieve a desired drying rate for wet materials. As it is usually impractical to measure moisture content directly, an extended Kalman filter (EKF) observer is used to estimate the moisture content on-line in order to detect the drying end-point and to provide a state estimate for feedback control. Studies show that the EKF observer and the GMC controller can provide satisfactory estimation and control of the particle moisture content even if the process model error is significant.

Incremental sheet forming (ISF) is a flexible method for forming sheet metal that can be considered as an incremental deformation process. It is applicable to low volume parts manufacturing and rapid prototyping. Existing models for ISF, which are predominantly based on standard finite element analysis software, are extremely slow and therefore not suitable for control engineering purposes. A fast method for modeling deformation in ISF is required that can form the basis of a model predictive control system to regulate the geometric accuracy of parts produced by the process. This paper proposes a model that is based on the numerical minimization of plastic energy within the material. By using a quadratic yield function to describe the yield surface, the minimization can be formulated as a Second Order Cone Programming (SOCP) optimization problem. This model is solved efficiently by the use of primal dual interior point SOCP algorithms.

This paper proposes a new fast method for determining plastic deformation of sheet metal. The method is applied to a flexible metal shaping process, incremental sheet forming (ISF), which is applicable to low volume manufacturing and rapid prototyping. Being able to predict the deformation of the sheet is a key requirement of a model predictive based control system to regulate the geometric accuracy of parts formed by the process. Existing models for ISF, which are predominantly based on finite element modeling, are slow since the model must be updated at every time step of the process. Other modeling approaches have combined plane-strain or shear deformation equations with approximate empirical relationships, but their accuracy is limited by the conditions under which these experimental relationships were obtained. Here, a fast executing model for the incremental forming process is proposed that is based on the numerical minimization of the plastic energy within the plate. The optimization can be formulated as a second order cone program (SOCP), which can be solved using efficient numerical methods.

For the last seven years, Oxford University and the Ford Motor Co. have been researching jointly the development of the large-scale spray forming of steel tooling capable for use in mass production, particularly for the pressing of sheet metal in automotive applications. These investigations have involved: comprehensive microstructure and property studies, modelling of shape evolution and heat flow, real-time feedback control of tool temperature to eliminate tool distortion, high speed imaging and particle image velocimetry of droplet deposition on 3D shapes, the testing of full-scale tools for different applications in the production environment, and detailed studies of the cost and time savings realised for different tooling applications. This paper will provide an overview of the scientific and technical progress to date, present latest results, and describe the current state-of-the-art. Many of the insights described have relevance and applicability across the family of thermal spray processes and applications.

This paper considers the problem of control system design for governing temperature profiles of a sprayform tooling process used in rapid manufacture. After describing and modelling the sprayforming process, the paper introduces the concept of steady-state functional controllability and investigates the degree up to which this process is controllable via multivariable controllers. In particular, the discrete time variant (DTV) linear quadratic regulators (LQR) are considered as examples of multivariable controllers. The theoretical issues outlined in this paper are accompanied by simulations and experimental studies of a real sprayforming process.

The paper shows how the multivariable problem of designing the dynamics of a cross-directional control system for a paper machine, can be reduced to choosing a single scalar dynamic term that will control a set of SISO loops. Uncertainties in the multivariable model of the plant can be expressed in terms of their effect on the SISO leaps, leading to a procedure for designing a robust control system. Robustness is achieved by adjusting a scalar parameter in a precompensator matrix, which has the effect of applying control actions to the actuators in the vicinity of an error, rather than changing the settings of all actuators.

Vacuum plasma spraying (VPS) is an industrial technique used to coat substrates with a wide range of materials for numerous applications. Historically, vacuum plasma spraying processes have been open-loop processes with, at most, closed-loop control of the spray parameters. Such processes would benefit from closed-loop control as the issues of process repeatability and coating quality could be addressed. This paper describes the modelling of a VPS process and presents a closed loop control strategy based on the model results.

This paper considers the processing of data collected by scanning gauges from industrial web processes such as metal rolling, coating, paper making and plastic film extrusion. It describes a method based upon the generalised sampling theorem for reconstructing two-dimensional variations in material properties from scanned data. The approach does not require any knowledge of the process apart from the bandwidth of the variations in the machine direction.

Most modern spray deposition processes, such as spray painting or coating, are automated by using a robot to move an applicator over the surface being sprayed. Determining the robot path that creates the required coat thickness over the surface can be considered as an optimisation problem, which traditionally has been solved in the spatial domain. In this paper, results from sampling theory are used to transfer the problem into the spatial frequency domain. These results are used to determine the optimal path for a spraying application. The paper also shows how angled raster patterns can be combined to provide a continuous path over the surface that generates the required distribution of deposited material.

In industrial web processes such as paper making, plastic film extrusion, metal rolling and coating, measurements of web properties are often obtained from gauges that scan backwards and forwards across the sheet. The measurements taken by a scanning gauges can be considered as 1-dimensional samples of a 2-dimensional variation. An extension of the generalised sampling theorem is used to reconstruct the underlying 2-dimensional variations in properties of the sheet from scanned data. The method is illustrated by results from a simulation. Strategies for implementing the technique are discussed.

This paper looks at the problem of understanding the measurements from two dimensional industrial processes such as paper manufacture or plastic film extrusion. It describes the difficulties of obtaining a sampled data measurement that is free from aliased components and goes on to describe different methods of measurement and how they can be matched to the spectrum of the web product. It outlines how an understanding of the spectral properties of scanned data can lead to the reconstruction of two dimensional data profile in a way which is superior to current practice. The paper concludes with a description of a special machine developed to test and compare different methods of establishing cross direction pro-files

Methods have been developed for monitoring the performance of SISO control systems, which compare the variance of the output achieved from the plant to an estimate of the variance that could be achieved by minimum variance control. The methods require knowledge of only the inherent delay within the process. This paper extends these ideas to analyze the performance of cross-directional control systems for sheet processes such as paper machines, which are large multivariable systems. Because such systems are inherently ill-conditioned, the performance is compared against that of a generalized minimum variance controller designed to avoid controlling poorly controllable spatial and dynamic modes. The results of applying the algorithm to data from a paper machine are presented.

This paper considers suitable disturbance models for use in web forming processes, it suggests a practical disturbance representation and using spectral factorisation presents a multivariable aggregated model. The paper compares Generalised Minimum Variance (GMV) controllers designed using uncorrelated and correlated disturbances. It demonstrates the improvement in performance of a multivariable GMV controller which is designed to accomodate the cross direction correlation in the disturbance, when compared with a scalar GMV controller which cannot take into account the effects of correlated disturbances.