The study of proteins and their function is key to understanding the intrinsic properties of the cell both in normal and disease states. An important part of this analysis involves the prediction and elucidation of three-dimensional protein structures, and the interactions they undertake, through the use of computational techniques. The majority of work in this thesis focuses on the effects that non-specific charge interactions have on these structures. Firstly, sets of proteins that select a single partner from closely related alternatives were analysed using an empirical binding model in order to identify a determinant for binding specificity. Here, we predicted that charge interactions are more favourable in the majority of cognate pairs, compared to other energetic and geometric properties. In addition to this, charged protein side-chains were found to be important with respect to phosphorylation sites that lie in disordered regions of proteins. The analysis of charge environments around these sites indicated a propensity for a subset of residues to be phosphorylated when surrounded by charged residues. This was especially true for proteins involved in RNA processing.An investigation of protein-mRNA interactions also identified a role for charge interactions that occur within translational control mechanisms. The correlation seen between positively charged disordered regions of specific regulatory proteins and the secondary structure of target mRNAs revealed a potential control mechanism that is partially influenced by polyelectrostatic interactions.

This thesis studies the optimal control of vehicular systems, focusing on the solution of minimum-lap-time problems for a Formula 1 car. The basic optimal control theory is summarised as an infinite-dimensional extension of optimisation theory. The relevant numerical techniques for optimisation and integral approximation are compared in view of the application to vehicle systems. The classical brachistochrone problem is revisited from an optimal control perspective, with two vehicle-relevant generalisations. Closed-form solutions are derived for both the optimal trajectory and transit time. Problems involving a steerable disc rolling on the interior surface of a hemisphere are studied. For three-dimensional problems of this type, which involve rolling bodies and nonholonomic constraints, numerical solutions are used. The identification of 3D race track models from measured GPS data is treated as a problem in the differential geometry of curves and surfaces. Curvilinear coordinates are adopted to facilitate optimal control solutions. The track is specified in terms of three displacement-dependent curvatures and two edge variables. The differential model is smoothed using numerical optimal control techniques. The Barcelona track is considered as an illustrative example. The minimum-lap-time problem for a Formula 1 car on a flat track is solved using direct transcription. The driven line and multiple car setup parameters are optimised simultaneously. It is shown that significant lap-time reductions can be obtained from track-specific setup parameter optimisation. Reduced computing times are achieved using a combination of analytical derivatives, model non-dimensionalisation and problem scaling. The optimal control of the car on a 3D track is studied; the results are compared with flat-track solutions. Contemporary kinetic energy-recovery systems are studied and compared with future hybrid kinetic-thermal energy-recovery systems. It is demonstrated that these systems can produce contemporary lap time using approximately two-thirds of the fuel required by present-day vehicles.

Co-rotating twin-screw extruders are unique and versatile machines that are used widely in the plastics and food processing industries. Due to the large number of operating variables and design parameters available for manipulation and the complex interactions between them, it cannot be claimed that these extruders are currently being optimally utilised. The most significant improvement to the field of twin-screw extrusion would be through the provision of a generally applicable dynamic process model that is both computationally inexpensive and accurate. This would enable product design, process optimisation and process controller design to be performed cheaply and more thoroughly on a computer than can currently be achieved through experimental trials. This thesis is divided into three parts: dynamic modelling, measurement and control. The first part outlines the development of a dynamic model of the extrusion process which satisfies the above mentioned criteria. The dynamic model predicts quasi-3D spatial profiles of the degree of fill, pressure, temperature, specific mechanical energy input and concentrations of inert and reacting species in the extruder. The individual material transport models which constitute the dynamic model are examined closely for their accuracy and computational efficiency by comparing candidate models amongst themselves and against full 3D finite volume flow models. Several new modelling approaches are proposed in the course of this investigation. The dynamic model achieves a high degree of simplicity and flexibility by assuming a slight compressibility in the process material, allowing the pressure to be calculated directly from the degree of over-fill in each model element using an equation of state. Comparison of the model predictions with dynamic temperature, pressure and residence time distribution data from an extrusion cooking process indicates a good predictive capability. The model can perform dynamic step-change calculations for typical screw configurations in approximately 30 seconds on a 600 MHz Pentium 3 personal computer. The second part of this thesis relates to the measurement of product quality attributes of extruded materials. A digital image processing technique for measuring the bubble size distribution in extruded foams from cross sectional images is presented. It is recognised that this is an important product quality attribute, though difficult to measure accurately with existing techniques. The present technique is demonstrated on several different products. A simulation study of the formation mechanism of polymer foams is also performed. The measurement of product quality attributes such as bulk density and hardness in a manner suitable for automatic control is also addressed. This is achieved through the development of an acoustic sensor for inferring product attributes using the sounds emanating from the product as it leaves the extruder. This method is found to have good prediction ability on unseen data. The third and final part of this thesis relates to the automatic control of product quality attributes using multivariable model predictive controllers based on both direct and indirect control strategies. In the given case study, indirect control strategies, which seek to regulate the product quality attributes through the control of secondary process indicators such as temperature and pressure, are found to cause greater deviations in product quality than taking no corrective control action at all. Conversely, direct control strategies are shown to give tight control over the product quality attributes, provided that appropriate product quality sensors or inferential estimation techniques are available.

Gun and gun turret systems are the primary units of the weapon systems of an aircraft. They are required to hit targets accurately during operations. That is why a complete, high precision control of weapon systems is required. This function is provided by accurate modeling of the system and the design of a suitable controller. This study presents the modeling of and controller design for the gun and turret system for an aircraft. For the controller design purpose, first the mathematical model of the system is constructed. Then the controller is designed to position the turret system as the target comes into sight. The reference input to the controller will either be obtained from a FLIR (Forward Looking Infrared) unit or from a HCU (Hand Control Unit). The basic specification for the controller is to hold theerror signal within the 5.5&deg / positioning envelope. This specification is satisfied by designing Linear Quadratic Gaussian and Internal Model Control type controllers. The performance of the overall system has been examined both by simulation studies and on the real physical system. Results have shown that the designed system is well over being sufficient.

Co-rotating twin-screw extruders are unique and versatile machines that are used widely in the plastics and food processing industries. Due to the large number of operating variables and design parameters available for manipulation and the complex interactions between them, it cannot be claimed that these extruders are currently being optimally utilised. The most significant improvement to the field of twin-screw extrusion would be through the provision of a generally applicable dynamic process model that is both computationally inexpensive and accurate. This would enable product design, process optimisation and process controller design to be performed cheaply and more thoroughly on a computer than can currently be achieved through experimental trials. This thesis is divided into three parts: dynamic modelling, measurement and control. The first part outlines the development of a dynamic model of the extrusion process which satisfies the above mentioned criteria. The dynamic model predicts quasi-3D spatial profiles of the degree of fill, pressure, temperature, specific mechanical energy input and concentrations of inert and reacting species in the extruder. The individual material transport models which constitute the dynamic model are examined closely for their accuracy and computational efficiency by comparing candidate models amongst themselves and against full 3D finite volume flow models. Several new modelling approaches are proposed in the course of this investigation. The dynamic model achieves a high degree of simplicity and flexibility by assuming a slight compressibility in the process material, allowing the pressure to be calculated directly from the degree of over-fill in each model element using an equation of state. Comparison of the model predictions with dynamic temperature, pressure and residence time distribution data from an extrusion cooking process indicates a good predictive capability. The model can perform dynamic step-change calculations for typical screw configurations in approximately 30 seconds on a 600 MHz Pentium 3 personal computer. The second part of this thesis relates to the measurement of product quality attributes of extruded materials. A digital image processing technique for measuring the bubble size distribution in extruded foams from cross sectional images is presented. It is recognised that this is an important product quality attribute, though difficult to measure accurately with existing techniques. The present technique is demonstrated on several different products. A simulation study of the formation mechanism of polymer foams is also performed. The measurement of product quality attributes such as bulk density and hardness in a manner suitable for automatic control is also addressed. This is achieved through the development of an acoustic sensor for inferring product attributes using the sounds emanating from the product as it leaves the extruder. This method is found to have good prediction ability on unseen data. The third and final part of this thesis relates to the automatic control of product quality attributes using multivariable model predictive controllers based on both direct and indirect control strategies. In the given case study, indirect control strategies, which seek to regulate the product quality attributes through the control of secondary process indicators such as temperature and pressure, are found to cause greater deviations in product quality than taking no corrective control action at all. Conversely, direct control strategies are shown to give tight control over the product quality attributes, provided that appropriate product quality sensors or inferential estimation techniques are available.

Crystallization is a key unit operation used for obtaining purified products by many process industries. The key properties of the crystalline products, such as size and shape distribution, purity and polymorphic form are controlled by the crystallization process. All these properties impact significantly the downstream operations such as drying or filtration. Therefore, monitoring and controlling this process is fundamental to ensure the quality of the final product. Process analytical technology (PAT) brings numerous new methods and opportunities in the process analytics and real time process monitoring systems, which can be integrated into the control algorithm and provide high level optimal control strategies as well as deeper understanding of the process. Process monitoring helps develop mathematical models which can, in one hand, help in better understanding the processes and consecvently the development and application of advanced control methods in order to achieve better product quality. In this work, image processing and image analysis based direct nucleation control (IA-DNC) is developed in order to investigate the evolution of the crystal properties, such as crystal size, and crystal shape distribution. The IA-DNC approach is also compared to alternative DNC techniques, in which particle number were measured by Focused Beam Reflectance Measurement (FBRM) in order to control crystal size. A control approach is introduced that control the nucleation and disappearance of crystals during cooling and heating segments related to the changes of the number of counts (measured by Particle Vision Measurment, so called PVM or combination of FBRM and PVM). The approach was applied to investigate crystallization of compounds with different behavior: potassium dihydrogen phosphate (KDP) water, contaminated KDP -water and Ascorbic acid water systems. The results demonstrate the application of imaging technique for model-free feedback control for tailoring crystal product properties. The second main aim of the thesis is to investigate and control crystallization processes in impure media in the presence of multiple impurities, with an impact on the crystal shape via growth kinetics. The broad impact of the crystal growth modifiers (impurities) on the growth kinetics is observed in real time by using in situ video imaging probe and real-time image analysis. A morphological population balance model is developed, which incorporates a multi-site, competitive adsorption mechanism of the impurities on the crystal faces. The kinetic parameters of primary nucleation, growth and impurity adsorption for a model system of potassium dihydrogen phosphate crystallization in water in the presence of two impurities, were estimated and validated with experimental results. It was demonstrated that the model can be used to describe the dynamic evolution of crystal properties, such as size and aspect ratio during crystallization for different impurity profiles in the system. Manual, feedback and hybrid feedback-feedforward control techniques are developed and investigated numerically for continuous processes, while model-based and model-free control approach for crystal shape are developed for batch processes. The developed morphological population balance model is implemented and applied in the model-based control approaches, which are suitable to describe multicomponent adsorption processes and their influence on the crystal shape. Case studies show the effectiveness of crystal growth modifiers based shape control techniques. Comparison of different control approaches shows the effectiveness of the techniques. The third part of the thesis deals with purification of crystals when adsorption of impurities on crystal surfaces and its incorporation into crystals are considered. A purification method, called competitive purity control (CPC) is proposed and investigated. A morphological population balance model, including nucleation, growth and competitive impurity adsorption kinetics is developed to describe the case when multiple impurities can adsorb competitively on the crystal surface. The model is also combined with liquid phase chemical reaction model, in order to investigate the purity control case when an additive is introduced in the system that reacts with the impurity forming a non-adsorbing reaction product. Both competitive purity control approaches proposed: the adsorption based competitive purity control (A-CPC) and the reaction based competitive purity control (R-CPC); are investigated using detailed numerical simulations then compared with the alternative widely used purification method, called recrystallization. In the last contribution chapter, an integrated process optimization of a continuous chemical reactor and crystallizer is performed and studied numerically. The purpose of this study is to show the way in which the byproduct produced in the chemical reactor may affect the crystallization process and how its negative effect can be reduced by applying integrated process optimization. Sensitivity analysis of the system was performed by considering the flow rate and the concentration of substances in the input stream of the chemical reactor as manipulated process variables. Model based integrated process optimization and the sensitivity analysis in order to obtain improved quality product in terms of crystal size, shape and purity.

The development of large lightweight airframes has resulted in what used to be high frequency structural dynamics entering the low frequency range associated with an aircraft’s rigid body dynamics. This has led to the potential of adverse interactions between the aeroelastic effects and flight control, especially unwanted when incidents involving failures or extreme atmospheric disturbances occur. Moreover, the pilot’s response in such circumstances may not be reproducible in simulators and unique to the incident. The research described in this thesis describes the development of a pilot model suitable for the investigation of the effects of aeroelasticity on manual control and the study of the resulting airframe loads. After a review of the state-ofthe- art in pilot modelling an experimental approach involving desktop based pilot-in-the-loop simulation was adopted together with an optimal control based control-theoretic pilot model. The experiments allowed the investigation of manual control with a nonlinear flight control system and the derivation of parameter bounds for single-input-single-output pilot models. It was found that pilots could introduce variations of around 15 dB at the resonant frequency of the open loop pilot-vehicle-system. Sensory models suitable for the simulation of spatial disorientation effects were developed together with biomechanical models necessary to capture biodynamic feedthrough effects. A detailed derivation and method for the application of the modified optimal control pilot model, used to generate pilot control action, has also been shown in the contexts of pilot-model-in-the-loop simulations of scenarios involving an aileron failure and a gust encounter. It was found that manual control action particularly exacerbated horizontal tailplane internal loads relative to the limit loads envelope. Although comparisons with digital flight data recordings of an actual gust encounter showed a satisfactory reproduction and highlighted the adverse affects of fuselage flexibility on manual control, it also pointed towards the need for more incident data to validate such simulations.

<p>Indoor air quality in office buildings can impact the health, well-being, and productivity of occupants. In most buildings, occupants exhaled breath is the primary source of carbon dioxide (CO₂). Concentrations of indoor CO₂ are also strongly associated with the operational mode of the mechanical ventilation system. While CO2 is routinely monitored in indoor environments, there are few spatially-resolved real-time measurements of CO₂ throughout mechanical ventilation systems. Such measurements can provide insight into indoor- and outdoor-generated CO₂ dispersion throughout a building and between the building and the outdoor atmosphere. This thesis aims to investigate spatiotemporal variations in CO₂ concentrations and mass fluxes throughout a mechanical ventilation system of a living laboratory office in a LEED-certified building. The impact of human occupancy patterns and ventilation conditions of CO₂ concentrations and fluxes was evaluated. </p> <p>A four-month measurement campaign was conducted in one of the four living laboratory offices at the Ray W. Herrick Laboratories. The living laboratory offices feature precise control and monitoring of the mechanical ventilation system via an advanced building automation system. Various mechanical ventilation modes were implemented, such as variable outdoor air exchange rates (AERs) and recirculation ratios. A novel multi-location sampling manifold was used to measure CO₂ at eight locations throughout the ventilation system, such as across the outdoor, supply, and return air ducts. Office occupancy was measured via a chair-based temperature sensor array. Volumetric airflow rate data and CO₂ concentration data were used to estimate CO₂ mass fluxes through the ventilation system. The CO₂ mass flux for the outdoor and exhaust air was used to evaluate the net CO₂ transport from the office to the outdoor atmosphere. </p> <p>The measurements demonstrate that there exist significant spatiotemporal variations in CO₂ concentrations across the outdoor, supply, and return air ducts. CO₂ concentrations varied with human occupancy in the office and the outdoor AER of the mechanical ventilation system. Due to human-associated CO₂ emissions, the net CO₂ mass flux from the office to the outdoor environment was approximately 700 kg of CO₂ per year. Thus, occupied offices may represent an important, yet unrecognized, source of CO₂ to the urban atmosphere.</p>

The trend of future wind farms moving further offshore requires much higher reliability for each wind turbine in order to reduce maintenance cost. The drive-train system and power electronic converter system have been identified as critical sub-assemblies that are subject to higher failure rates than the other sub-assemblies in a wind turbine. Modern condition monitoring techniques may help schedule the maintenance and reduce downtime. However, when it comes to offshore wind turbines, it is more crucial to reduce the failure rates (or reduce the stresses) for the wind turbines during operation since the harsh weather and a frequently inaccessible environment will dramatically reduce their availability once a failure happens. This research examines the mechanical, electrical and thermal stresses in the sub-assemblies of a doubly-fed induction generator (DFIG) wind turbine and how to reduce them by improved control strategies. The DFIG control system (the rotor-side and the grid-side converter control) as well as the wind turbine control system are well established. The interactions of these control systems have been investigated. This research examines several further strategies to reduce the mechanical and electrical stresses. The control system's coordination with the protection schemes (crowbar and dc-chopper) during a grid fault is presented as well. An electro-thermal model of the power converter has been developed to integrate with the DFIG wind turbine model, for the evaluation of the thermal stresses under different operating states and control schemes. The main contributions of this thesis are twofold. A first contribution is made by providing all the control loops with well-tuned controllers in a more integrated methodology. The dynamics of these controllers are determined from their mathematical models to minimize the interference between different control-loops and also to reduce the electrical transients. This thesis proposes a coordination strategy for the damping control, pitch control and crowbar protection which significantly reduces the mechanical oscillations. On the other hand, an integrated model of the wind turbine and converter electro-thermal system is established that can illustrate the performance integration with different control strategies.

Active Queue Management (AQM) schemes are used for ensuring the Quality of Service (QoS) in telecommunication networks. However, they are sensitive to parameter settings and have weaknesses in detecting and controlling congestion under dynamically changing network situations. Another drawback for the AQM algorithms is that they have been applied only on the Markovian models which are considered as Short Range Dependent (SRD) traffic models. However, traffic measurements from communication networks have shown that network traffic can exhibit self-similar as well as Long Range Dependent (LRD) properties. Therefore, it is important to design new algorithms not only to control congestion but also to have the ability to predict the onset of congestion within a network. An aim of this research is to devise some new congestion control methods for communication networks that make use of various traffic characteristics, such as LRD, which has not previously been employed in congestion control methods currently used in the Internet. A queueing model with a number of ON/OFF sources has been used and this incorporates a novel congestion prediction algorithm for AQM. The simulation results have shown that applying the algorithm can provide better performance than an equivalent system without the prediction. Modifying the algorithm by the inclusion of a sliding window mechanism has been shown to further improve the performance in terms of controlling the total number of packets within the system and improving the throughput. Also considered is the important problem of maintaining QoS constraints, such as mean delay, which is crucially important in providing satisfactory transmission of real-time services over multi-service networks like the Internet and which were not originally designed for this purpose. An algorithm has been developed to provide a control strategy that operates on a buffer which incorporates a moveable threshold. The algorithm has been developed to control the mean delay by dynamically adjusting the threshold, which, in turn, controls the effective arrival rate by randomly dropping packets. This work has been carried out using a mixture of computer simulation and analytical modelling. The performance of the new methods that have.