In this thesis work, a mobile robot is designed to be used in search and rescue operations to help the human rescue workers. The difficult physical conditions in the ruins obstruct the movement. Therefore, it is aimed to design a search and rescue robot which can move easily on rough terrain and climb over the obstacles. The designed robot is made up of three modules. A connecting unit is designed that is situated between each module. This connecting unit which is composed of two universal and one revolute joint gives 5 DOF relative motions to the modules. On the other hand, the wheel&rsquo / s continuous contact with the ground is important while moving on rough terrain. In order to increase the adaptation of the robot to the rough terrain the rear axle is connected to the body with a revolute joint. Besides, skid steering system is used in the design of the robot to attain a compact and light solution which requires few parts. In the study, kinematic equations and dynamic equations of the robot are obtained to be used by the control program. The dynamic equations are obtained by using the Newton &ndash / Euler formulation. The forces, which are transmitted by the connecting unit to the modules, and the reaction forces formed between the wheels and the ground are derived by using these equations. &ldquo / Follow-the-Leader approach&rdquo / is used as a control strategy to make the modules move in formation and to reduce the tracking problem. In this approach, the first module is the leader and the second and third modules follow it. A Matlab program is written to control the robot by using the constructed mathematical model of the robot. The reaction forces between the wheels and the ground are calculated through using the Matlab program written. Moreover to make the simulations of the robot for some cases, a model is constructed in ADAMS program.

Traditional macroeconometric models of the Australian economy estimate the behaviour of wage and price inflation separately, thereby ignoring the possibility that there is a contemporaneous relationship between these two variables. This thesis follows a recent trend emerging in other small open economies, such as the UK and Norway, which is to estimate the behaviour of wage and price inflation in a simultaneous-equations model. In order to capture the behaviour of the major variables which drive wages and prices, a complete model is constructed which embeds these important transmission channels. The model is developed in three stages. First, underpinned by a theoretical framework of a unionized economy with imperfect competition, the core wage- price system is developed whereby consumer prices and average weekly earnings are jointly estimated in a simultaneous-equations framework. Particular atten- tion is given to estimating two identified cointegrating relationships for wages and prices. These equations are interpreted as the long-run targets of workers and firms respectively and are embedded in a parsimonious system of short-run dynamics which drive wages and prices towards their long-run levels. Second, llie behaviour of llie main feedback variables driving llie wage-price system is modelled, with particular attention given to the unemployment rate. While several of the most recent models of unemployment show that the aggregate unemployment rate in Australia does indeed behave differently during periods of low and high unemployment, none can explain what drives the unemployment rate to increase at such a rapid rate and what contributes to its much slower decrease. Another central issue of this thesis, therefore, is to propose a rationale for this as yet unexplained phenomenon. The remaining behavioural variables in the model, including aggregate labour productivity, domestic output and the real exchange rate, are all estimated in a single-equation framework. Third, these equations are then combined with a number of important identi- ties and an interest-rate reaction function to close the model. Then, the impacts of several simulated economic scenarios on Australia's economic landscape are considered. Special emphasis is given to analysing the impact of a large nomi- nal wage shock. The outcomes from these simulated scenarios are pertinent to understanding the inflation process and have important implications for a small open economy like Australia with an explicit inflation target. Overall, the major result to emerge from this thesis is that there is significant statistical support for the hypothesis that wage and price inflation in Australia are jointly determined. This phenomenon has not yet been fully exploited in current macroeconometric models of the Australian economy. The modelling exercise also reveals that the Australian unemployment rate is linear in demand and labour productivity shocks, with nonlinear behaviour caused by real wage rigidity and generous unemployment benefits. Importantly, this simple model is able to simulate the behaviour of the Australian economy extremely well. The outcome from the policy scenarios is clear: both demand-side and supply-side shocks have real and nominal effects on the economy in the short- to medium- run, ceteris paribus. Moreover, a large nominal wage shock to the economy, which results in a real wage rise, will have no sustained effect on the level of domestic activity in the economy, the inflation rate or the real exchange rate. Unemployment is, however, pushed slightly above equilibrium in the short- to medium-run due to a sustained higher real wage level.

In capital market research (CMR) studies of the value relevance of accounting numbers are founded upon the concept that, in equilibrium, the book values are equal to or have some long-term relationship with the market value and that market returns are related to book returns. This thesis seeks to resolve a gap in the CMR by examining 30 selected individual firms listed on the Australian stock market during the period 1950 to 2004, using equilibrium correction modelling techniques. Even these limited prior works used cross-sectional techniques rather than the long-run, time-series, analysis used in this study. Moreover, dynamic analysis in the CMR has tended to focus on indexes or portfolio data rather than using firm-specific case study data of the type modelled here. No prior research has taken this approach using Australian data. The results of this thesis indicated that an equilibrium correction relationship between market values and book values for firms listed on the Australian Stock Exchange (ASX) could be determined by using accounting and macroeconomic regressors. The findings of the thesis were consistent with the literature in terms of the variables suggested and important in the firm's valuation from the three main approaches, the analysts (industry) approach, the finance and accounting theory (textbook) approach and the CMR literature approach. The earnings, dividends and book value variables are significant in their relationships with the firm's market values. The models constructed were typically more informative and had an increased forecasting performance compared with the a priori models tested, based on theory and the literature.

The technology of UAV (Unmanned Aerial Vehicle) has developed since its conception many years ago. UAVs have several features such as, computerised and autonomous control without the need for an on-board pilot. Therefore, there is no risk of loss of life and they are easier to maintain than manned aircraft. In addition, UAVs have an extended range/endurance capability, sometimes for several days. This makes UAVs attractive for missions that are typically

An essential step to achieving human-machine speech communication with the naturalness of communication between humans is developing a machine that is capable of recognising emotions based on speech. This thesis presents research addressing this problem, by making use of acoustic and prosodic information. At a feature level, novel group delay and weighted frequency features are proposed. The group delay features are shown to emphasise information pertaining to formant bandwidths and are shown to be indicative of emotions. The weighted frequency feature, based on the recently introduced empirical mode decomposition, is proposed as a compact representation of the spectral energy distribution and is shown to outperform other estimates of energy distribution. Feature level comparisons suggest that detailed spectral measures are very indicative of emotions while exhibiting greater speaker specificity. Moreover, it is shown that all features are characteristic of the speaker and require some of sort of normalisation prior to use in a multi-speaker situation. A novel technique for normalising speaker-specific variability in features is proposed, which leads to significant improvements in the performances of systems trained and tested on data from different speakers. This technique is also used to investigate the amount of speaker-specific variability in different features. A preliminary study of phonetic variability suggests that phoneme specific traits are not modelled by the emotion models and that speaker variability is a more significant problem in the investigated setup. Finally, a novel approach to emotion modelling that takes into account temporal variations of speech parameters is analysed. An explicit model of the glottal spectrum is incorporated into the framework of the traditional source-filter model, and the parameters of this combined model are used to characterise speech signals. An automatic emotion recognition system that takes into account the shape of the contours of these parameters as they vary with time is shown to outperform a system that models only the parameter distributions. The novel approach is also empirically shown to be on par with human emotion classification performance.

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.

With an increased urgency for global action towards climate change mitigation, this research was undertaken with the aim of evaluating post-combustion CO2 capture as an emission abatement strategy for gas-fired power plants. A dynamic rate-based model of a capture plant with MEA solvent was built, with imposed chemical equilibrium, and validated at pilot scale under transient conditions. The model predicted plant behaviour under multiple process inputs and disturbances. The validated model was next used to analyse the process and it was found that CO2 absorption is mass transfer limited. The model was then improved by explicitly adding reactions rate in the model continuity, the first such dynamic model to be reported for the capture process. The model is again validated and is observed to provide better predictions than the previous model. Next, high fidelity models of a gas-fired power plant, a scaled-up capture plant and a compression train were built and integrated for 90% CO2 capture. Steam for solvent regeneration is extracted from the power plant IP/LP crossover pipe. Net efficiency drops from 59% to 49%, with increased cooling water demand. A 40% exhaust gas recirculation resulted in a recovery of 1% efficiency, proving that enhanced mass transfer in the capture plant reduces solvent regeneration energy demands. Economic analysis reveals that overnight cost increases by 58% with CO2 capture, and cost of electricity by 30%. While this discourages deployment of capture technology, natural gas prices remain the largest driver for cost of electricity. Other integration approaches – using a dedicated boiler and steam extraction from the LP steam drum – were explored for operational flexibility, and their net efficiencies were found to be 40 and 45% respectively. Supplementary firing of exhaust gas may be a viable option for retrofit, as it is shown to minimise integrated plant output losses at a net efficiency of 43.5%. Areas identified for further study are solvent substitution, integrated plant part load operation, flexible control and use of rotating packed beds for CO2 capture.

Made available in DSpace on 2014-06-11T19:28:33Z (GMT). No. of bitstreams: 0 Previous issue date: 2008-12-16Bitstream added on 2014-06-13T20:37:37Z : No. of bitstreams: 1 silvaneto_am_me_guara.pdf: 692597 bytes, checksum: 5f3caf79f195676ad932f7c214821ffc (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / O estudo de um modelo matemático completo, incluindo os servos atuadores, a dinâmica do corpo rígido e o planejamento e geração de trajetórias do manipulador robótico cilíndrico, é um indispensável ponto de partida para aplicações de simulação das juntas e controle de movimentos. As equações cinemáticas obtidas pelas técnicas da Matriz de Transformação Homogênea e Matriz de Transformação Inversa são a solução para a geração de trajetórias, as quais podem ser feitas no espaço cartesiano ou no espaço das juntas e também possibilitam gerar o volume de trabalho do manipulador, que é de grande interesse para a especificação de determinada configuração em aplicações ou tarefas específicas. As equações de movimento foram derivadas usando a formulação Lagrangiana para predizer o comportamento do manipulador quanto à influência da geometria e os parâmetros de massa do manipulador. / The study of a complete mathematical model including the servos actuators, the dynamics of the body rigid and the planning and generation of the manipulator's cylindrical robotic trajectories is an indispensable starting point for applications of simulation of the joints and control of movements. The Kinematic equations obtained by the techniques Homogeneous Transformation Matrix and Inverse Transformation Matrix make is the solution for generation of trajectories that can be done in the cartesian space or in the space of the joints and they also make possible to generate the volume of the manipulator's work that is of great interest for specification certain configuration in applications or specific tasks. The movement equations were derived using the formulation Lagrangiana to predict the manipulator's behavior as for the influence of the geometry and the parameters of the manipulator's mass.

With an increased urgency for global action towards climate change mitigation, this research was undertaken with the aim of evaluating post-combustion CO2 capture as an emission abatement strategy for gas-fired power plants. A dynamic rate-based model of a capture plant with MEA solvent was built, with imposed chemical equilibrium, and validated at pilot scale under transient conditions. The model predicted plant behaviour under multiple process inputs and disturbances. The validated model was next used to analyse the process and it was found that CO2 absorption is mass transfer limited. The model was then improved by explicitly adding reactions rate in the model continuity, the first such dynamic model to be reported for the capture process. The model is again validated and is observed to provide better predictions than the previous model. Next, high fidelity models of a gas-fired power plant, a scaled-up capture plant and a compression train were built and integrated for 90% CO2 capture. Steam for solvent regeneration is extracted from the power plant IP/LP crossover pipe. Net efficiency drops from 59% to 49%, with increased cooling water demand. A 40% exhaust gas recirculation resulted in a recovery of 1% efficiency, proving that enhanced mass transfer in the capture plant reduces solvent regeneration energy demands. Economic analysis reveals that overnight cost increases by 58% with CO2 capture, and cost of electricity by 30%. While this discourages deployment of capture technology, natural gas prices remain the largest driver for cost of electricity. Other integration approaches – using a dedicated boiler and steam extraction from the LP steam drum – were explored for operational flexibility, and their net efficiencies were found to be 40 and 45% respectively. Supplementary firing of exhaust gas may be a viable option for retrofit, as it is shown to minimise integrated plant output losses at a net efficiency of 43.5%. Areas identified for further study are solvent substitution, integrated plant part load operation, flexible control and use of rotating packed beds for CO2 capture.

Dense medium separation (DMS) plants are typically used to beneficiate run-of-mine (ROM) coal in coal metallurgy. These plants normally make use of a dense medium cyclone as the primary processing unit. Because of the deviations in the ROM quality, the production yield and quality become difficult to maintain. A control system could benefit such operations to maintain and increase product throughput and quality. There are many different methods for developing a control system in a metallurgical operation; however, what is most fundamental is the use of a mathematical model to design a controller. For this reason, a first principle dynamic mathematical model has been developed for a DMS circuit. Each unit operation is modelled individually, then integrated together to form the complete system. The developed DMS circuit dynamic model is then used to simulate the process. It is also found that most models developed for DMS operations typically make use of steady-sate analysis and that very little literature is available on dynamic models of this kind. Difficulties that arise when validating a model in metallurgical processes are insufficient measurement points or the challenges in measuring certain variables, such as physical properties (e.g. particle size) or chemical components (e.g. ash percentage). This paper also explains how the Runge-Kutta approximation can be used in simulating DMS unit processes with intermediate online measurements that may be available. This can ultimately assist in verifying the accuracy of the simulation. One of the other problems that can occur when developing models from first principles is the estimation of model parameters. Specifically when non-linear state-space relationships are developed, one must ensure that there is a unique solution for the parameters in question. A method employing parameter identifiability is also presented in this dissertation to illustrate its use. In addition the process of estimating parameters is explained and illustrated. Copyright / Dissertation (MEng)--University of Pretoria, 2010. / Electrical, Electronic and Computer Engineering / unrestricted